仕訳帳情報
AI
https://www.mdpi.com/journal/ai
出版社:
MDPI
ISSN:
2673-2688
閲覧:
517
追跡:
0

論文募集
Aims

AI (ISSN 2673-2688) is an international and interdisciplinary scholarly open access journal on artificial intelligence. It publishes original research articles, reviews, communications, that offer substantial new insight into any field of study that involves artificial intelligence (AI), including machine and deep learning, knowledge reasoning and discovery, automated planning and scheduling, natural language processing and recognition, computer vision, robotics, and artificial general intelligence. There is no restriction on the length of the papers. Our aim is to encourage scientists and engineers to publish their experimental and theoretical research in as much detail as possible. Full experimental details and/or study methods must be provided for research articles so that the results can be reproduced.

Scope

    AI Theory
    AI Technique
    AI Application
    Intelligent machine/agent
    Knowledge representation
    Knowledge reasoning
    Machine learning
    Deep learning
    Computer vision
    Planning
    Robotics
    Natural language processing
    Artificial neural networks
    Evolutionary computing
    Probabilistic computing
    Genetic algorithms
    Fuzzy logic
    Expert systems

Other Keywords: reinforcement learning; data science; machine perception; machine recognition; automated reasoning and inference; case-based reasoning; reasoning under uncertainty; knowledge engineering; data mining; knowledge discovery; speech recognition; multi-agent planning; multi-agent systems; automated planning and scheduling; information retrieval; text mining; question answering; machine translation; smart computer programs; AI software development; heuristic search; human interfaces; intelligent robotics; motion and manipulation; affective computing; robotic systems; neuromorphic computing; human–machine interaction; multi-sensor; ethical machines; artificial consciousness; robot rights; AI logistics; automotive AI; data mining; AI medical diagnosis; AI healthcare; big data; AI military; AI testing; etc.
最終更新 Dou Sun 2020-05-07
Special Issues
Special Issue on Artificial Intelligence for Cybersecurity: A Data-Driven Approach
提出日: 2020-08-15

Dear Colleagues, As cyber-attacks grow in volume and complexity, artificial intelligence (AI) is helping under-resourced security operations analysts to stay ahead of threats. AI technologies like machine learning and natural language processing enable analysts to respond to threats with greater confidence and speed. AI is trained by consuming billions of data artifacts from both structured and unstructured sources. Through machine learning and deep learning techniques, AI improves its knowledge to “understand” cybersecurity threats and cyber risk. AI gathers insights and uses reasoning to identify the relationships between threats, such as malicious files, suspicious IP addresses or insiders. This analysis takes seconds or minutes, allowing security analysts to respond to threats up to 60 times faster. AI eliminates time-consuming research tasks and provides curated analysis of risks, reducing the amount of time security analysts take to make the critical decisions and launch an orchestrated response to remediate the threat. Therefore, the investigation on AI-based security is attracting more and more attention from both industry and academia. The central theme of this Special Issue is to investigate novel methodologies and theories for cybersecurity and privacy. In particular, this Special Issue focuses on addressing the usage of data mining, machine learning, and novel intelligent techniques for analyzing the data produced by any system and sensor network, and to emphasize the role of the AI in the security world. Topics of Interest: This Special Issue aims to present the most important and relevant advances to overcome the new challenges related to the application of AI for cybersecurity, through data mining, machine learning, deep learning, and cognitive computing. We seek original and high-quality submissions related to, but not limited to, one or more of the following topics: Cybersecurity AI solutions; Intrusion and detection AI-based techniques; Machine learning-based data analytics; Real-time data processing; Nature-inspired evolutionary algorithms and systems for pattern recognition, data analysis, and modeling; Pattern recognition and classification for multivariate time series; Learning from data streams; Learning from networked data; Deep Learning-based solutions; Algorithmic developments and applications of machine learning and data mining for Big Data; Distributed data mining and machine learning systems; Distributed computing and computing framework. Dr. Gianni D'Angelo Guest Editor Manuscript Submission Information Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AI is an international peer-reviewed open access quarterly journal published by MDPI. Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
最終更新 Dou Sun 2020-05-07
Special Issue on Solving Real Problems – Computerization and IT Technologies
提出日: 2020-08-15

Dear Colleagues, Computerization is entering into all areas of research. Effective solutions to real problems are possible thanks to the creation and development of new IT technologies enabling modeling and optimization of nonlinear and dynamic processes representing practically all areas of life. These new technologies are based on neural networks, fuzzy sets, and genetic algorithms, which are key artificial intelligence solutions. It seems that the basic problems of everyday life concern primarily health, finances, and the environment. Within each of these areas, these mentioned methods of artificial intelligence can be successfully used to solve the specific problems. Such detailed issues include, for example, in the field of medicine—diagnosis and determination of therapies for cancer and neurological diseases; in the field of finances—support of audit of financial statements of enterprises; in the field of environmental protection—management of water supply companies in order to reduce water losses, improve the quality of drinking water, or reduce pollution in treated wastewater. There are only a few examples from the three research areas where the number of problems that can be successfully solved using artificial intelligence methods in these three areas alone can be much greater, for example, as follows: support for therapy and diagnosis in the case of mental illnesses or forecasting and reduction of atmospheric pollutants. The problems that hinder the solution of these issues are not the IT tools that enable their solution, but finances in addition to social and individual resistance to their application. The latter problem, in particular, is difficult to overcome as it usually results from a lack of knowledge and psychological resistance on the part of decision-makers in changing from the comfort of maintaining the status quo. And, while financial issues and issues related to lack of knowledge can be solved relatively effectively, the issues related to the psychology of individuals are extremely difficult to overcome and very time-consuming, as can be seen even nowadays in the case of environmental pollution with plastic packaging and in the case of actions taken to prevent global warming. Dr. Jan Studziński Guest Editor Manuscript Submission Information Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AI is an international peer-reviewed open access quarterly journal published by MDPI. Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions. Keywords machine learning deep learning fuzzy set logic genetic algorithms for optimization human–computer interface affective computing environmental informatics computer-aided disease diagnosis computer-aided accounting
最終更新 Dou Sun 2020-05-07
Special Issue on Artificial Intelligence in Robotics Navigation
提出日: 2020-08-31

Dear Colleagues, Robotic positioning and navigation is an established research field topic: emerging indoor positioning technologies, like Wi-Fi or BLE fingerprinting or visible light communications, are introducing newcomers to this research field. Although there are many well-know deterministic and probabilistic models for indoor positioning technologies, some novel approaches are using state-of-the-art machine and deep learning models to find hidden patterns in the raw data, improve knowledge on this topic, and reduce positioning errors. This Special Issue encourages authors, from academia and industry, to submit new research results about positioning and navigation models based on machine learning for robotic systems. The Special Issue topics include but are not limited to the following: Fingerprint-based positioning; Inertial-based positioning; Positioning-based visible light communications; Angle of arrival determination; Clustering; Anomaly detection; Regression; Sensor fusion; Collaborative positioning; Novel applications based on machine/deep learning and positioning data. Dr. Joaquín Torres-Sospedra Dr. María Carmen Pérez Dr. Christopher Mutschler Guest Editors Manuscript Submission Information Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AI is an international peer-reviewed open access quarterly journal published by MDPI. Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
最終更新 Dou Sun 2020-05-07
Special Issue on Artificial Intelligence in the Smart Everything and Everywhere Era
提出日: 2020-08-31

Dear Colleagues, Companies and the industrial sector are adapting their products, services, processes, and business models to the new digital era. We have already crossed the door step of the 4th Industrial Revolution and so-called Industry 4.0 is transforming our economy and society by satisfying customers’ needs in a timely fashion. Advertising on the internet is also now more focused on our habits and needs, targeting the products we are demanding. Additionally, IoT technologies have joined our daily lives, enabling smart homes and e-health solutions for ageing in place- and ambient-assisted living. Even, the cities are using state-of-the-art technologies for smart and crowdsourced pollution monitors, processing open data, and engaging citizens in decision making. The new smart paradigms have something in common: they are built on top of a multitude of available data that need to be processed. This is where traditional machine learning and state-of-the-art deep learning techniques are playing a key role in finding hidden relations, and are making sense of the huge volumes of data collected by companies, organizations. and governments. This Special Issue encourages authors, from academia and industry, to submit new research results about technological innovations and novel applications for smart-anything based on machine and/or deep learning. The Special Issue topics include but are not limited to the following: Smart cities; Smart factories; Smart farming; Ambient-assisted living; Ageing in place; Big data; Deep learning; Internet of Things; Security; Privacy. Dr. Joaquín Torres-Sospedra Dr. Sergio Trilles Oliver Guest Editors Manuscript Submission Information Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AI is an international peer-reviewed open access quarterly journal published by MDPI. Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
最終更新 Dou Sun 2020-05-07
Special Issue on Applications of Artificial Intelligence in Metallurgical Process for Automation, Optimization and Control
提出日: 2020-08-31

Dear Colleagues, Continuous improvement of all metal production processes to simultaneously achieve higher quality standards while maintaining higher production yields is an essential task for contemporary metal producers. A huge amount of data is generated from various operating units, such as planning, process design, materials, assembly, production, quality, process control, scheduling, fault detection, shutdown, customer relation management, and so on. All this information is compiled and documented in the form of various databases and data warehouses. Machine Learning and Artificial Intelligence are robust tools for trend hunting and pattern recognition and can be a game-changer in achieving precise process control in each unit operation of ferrous and nonferrous industries. To take advantage of this technique, various metal industries have started to invest in different data mining technologies to search for hidden patterns, which can be used to enhance product quality and reduce cost and maintenance by artificial intelligence. In this issue, we will focus on Applications of Artificial Intelligence in Metallurgical Process for Automation, Optimization, and Control. In 2019, the APC will be fully subsidized by MDPI. Dr. Kinnor Chattopadhyay Guest Editor Manuscript Submission Information Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AI is an international peer-reviewed open access quarterly journal published by MDPI. Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions. Keywords Deep learning Level 2 automation Process control Machine Learning ANN
最終更新 Dou Sun 2020-05-07
Special Issue on Evolutionary Algorithms: Innovations and Applications
提出日: 2020-09-15

Dear Colleagues, For over 50 years, evolutionary computation has been widely used to obtain effective solutions to a large variety of problems which are computationally hard, and for which ad hoc heuristics might not exist. Since the origins of evolutionary algorithms, novel nature-inspired algorithms have been presented and successfully applied to real-world problems. Although the field is already established and has achieved a mature degree of development, innovations are still presented year after year, either proposing new techniques or improving certain aspects of well-known algorithms. Beyond these theoretical contributions, evolutionary algorithms are used every day to solve new industrial applications and problems. This Special Issue on Evolutionary Algorithms: Innovations and Applications calls for manuscripts describing theoretical contributions, innovations, advances, and novel applications of evolutionary computation and any biologically-inspired artificial intelligence techniques. We invite researchers to contribute original research papers devoted to advance in this field. Some techniques relevant to the Special Issue include but are not limited to the following: Genetic algorithms; Evolutionary programming; Evolution strategies; Genetic programming; Particle swarm optimization; Ant colony optimization; Memetic algorithms; Cultural algorithms; Hybrid evolutionary algorithms; Agent-based evolutionary approaches; Novel biologically-inspired algorithms. Dr. Rafał Dreżewski Dr. Alejandro Baldominos Guest Editors Manuscript Submission Information Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AI is an international peer-reviewed open access quarterly journal published by MDPI. Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions. Keywords Evolutionary computation Evolutionary algorithms Biologically-inspired artificial intelligence Metaheuristics Genetic algorithms Genetic programming Evolution strategies Evolutionary programming Particle swarm optimization Ant colony optimization Memetic algorithms Cultural algorithms
最終更新 Dou Sun 2020-05-07
Special Issue on Neural Architecture Search
提出日: 2020-09-15

Dear Colleagues, In recent years, Deep Learning has quickly been becoming a de facto standard for solving real world problems of very diverse kinds. Techniques such as convolutional neural networks are outstanding performers when tackling computer vision problems, LSTMs and other recurrent architectures are proficiently solving natural language processing and understanding problems, and deep learning is in general being considered as a promising approach for many other domains, including games or medicine. However, a problem remains inherent to the use of deep learning techniques: Designing a functional architecture remains not an easy task. The process generally involves large amounts of trial-and-error to find suitable architectures that attain a reasonable performance in the problem of choice. In this context, neural architecture search unveils as a useful alternative for automatically finding good-performing topologies. Further, the search procedure can be extended to also find optimal hyperparameters for the learning process. This Special Issue on Neural Architecture Search calls for manuscripts describing innovations and novel applications of neural architecture search. We invite researchers to contribute original research papers devoted to advance in this field. Topics relevant to the Special Issue include but are not limited to the following: Neuroevolution of deep learning architectures; Novel search methods for architecture optimization; Self-tuning of learning parameters; Automatic discovery of novel deep learning architectures; Multiobjective optimization in deep learning networks; Automatic performance optimization in deep learning; Evolution or optimization of adversarial models; Collaborative or competitive evolution in deep learning; Applications of neural architecture search. Dr. Alejandro Baldominos Dr. Alejandro Martín Guest Editors Manuscript Submission Information Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AI is an international peer-reviewed open access quarterly journal published by MDPI. Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions. Keywords Neural architecture search Deep learning Neural networks Neuroevolution Artificial intelligence
最終更新 Dou Sun 2020-05-07
Special Issue on Recognition of Human Emotions Using Machine Learning and Deep Learning Algorithms
提出日: 2020-09-30

Dear Colleagues, Emotion is a psycho–physiological response triggered by conscious and/or unconscious stimuli. Emotion cannot be explained by scientific principles such as rational thought, logical arguments, testable hypotheses, and repeatable experiments. Emotions play a crucial role in human communication and can be expressed by multidimensional cues, such as vocabulary, intonation of voice, facial expressions, and gestures. The recognition of emotions in the affective computing scenario may lead to understanding human cognitive processes, such as attention, memory, and decision making. For instance, (i) modeling emotional feelings and (ii) considering their behavioral implication (i.e., stress-related implications) are useful in preventing emotions from having a negative effect on the workplace. Accordingly, the decision-making process should discard emotion whenever possible: Both positive and negative emotions can distort the validity of a decision. Machine learning and deep learning techniques have already been applied to consistently recognize human emotion using physiological data, facial expression, body gestures, speech, and text. However, several challenges are still present. The learning model should be robust against high dimensional and heterogeneous data, unbalanced classes, and time ambiguity. For instance, modeling and predicting the emotional state over time is not a trivial problem, because continuous data labeling is costly and not always feasible. This is a crucial issue in real-world applications, where the labeling of the features is sparse and eventually describes only the most prominent emotional events. This Special Issue on “Recognition of Human Emotions Using Machine Learning and Deep Learning Algorithms” calls for manuscripts proposing new machine learning and deep learning methods, approaches, and applications able to face the challenges related to human motion recognition. Manuscripts focused on interpretable models which also provide explanations as to why and how the learning model achieved a prediction are particularly welcome. Dr. Luca Romeo Dr. Sara Moccia Guest Editors Manuscript Submission Information Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AI is an international peer-reviewed open access quarterly journal published by MDPI. Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions. Keywords Emotion recognition Affective computing Machine learning Deep learning Stress recognition
最終更新 Dou Sun 2020-05-07
Special Issue on Artificial Intelligence on Business Intelligence
提出日: 2020-10-30

Dear Colleagues, The explosion of data and computational power has been a key determinant in the development of Artificial Intelligence (AI), including machine learning and especially deep learning in recent years. AI methods have become increasingly popular as a methodological tool to understand complex data and offer intelligent processing to help people to save time and effort. Artificial Intelligence on Business Intelligence are difficult fields and bring great benefits. Many issues, such as customer lifetime value modeling, churn customer modeling, dynamic pricing, customer segmentation, recommendation systems, stock price prediction, etc., have been proposed and researched to help the community gain more benefits. This Special Issue aims at collecting high-quality papers on recent advances and reviews that address the challenge of Artificial Intelligence on Business Intelligence. Topics of interest include but are not limited to: Machine learning theory and applications; Deep learning and applications; Class imbalanced problem; Data mining approaches; Knowledge-based systems; Expert system. Dr. Tuong Le Guest Editor Manuscript Submission Information Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AI is an international peer-reviewed open access quarterly journal published by MDPI. Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions. Keywords machine learning neural networks deep learning class imbalanced problem data mining
最終更新 Dou Sun 2020-05-07
Special Issue on Artificial Intelligence in Agriculture
提出日: 2020-12-31

Dear Colleagues, Over the last decades, several emerging technologies and techniques have been developed for precision agriculture application. Artificial neural networks and deep learning algorithms are increasingly used in remote sensing and machine vision applications. Deep convolutional neural networks (CNNs) are the most widely used deep learning approach for image recognition. These methods have achieved dramatic improvements in many domains, and have attracted considerable interest from both academic and industrial communities. This Special Issue focuses on the recent advances in artificial intelligence applications in agriculture and natural resources. For this purpose, we invite researchers to contribute original research papers in the areas of machine and computer vision, Internet of things, big data analytics, automation and robotics, machine learning, deep and transfer learning, reinforcement learning, logistics and optimization, and so on. Potential Topics include, but are not limited to, the following: Remote sensing UAV applications in agriculture Machine and computer vision Automatic tools for disease and pest detection High-throughput phenotyping tools Yield prediction techniques Big data analytics Precision agriculture Digital and smart agriculture and machinery Decision support systems, crop modeling, and optimization Agroclimatology. Dr. Yiannis Ampatzidis Dr. Spyros Fountas Dr. Wonsuk (Daniel) Lee Dr. Panos Pardalos Guest Editors Manuscript Submission Information Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AI is an international peer-reviewed open access quarterly journal published by MDPI. Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
最終更新 Dou Sun 2020-05-07
Special Issue on Artificial Intelligence and Machine Learning for Intelligent Sensing and Signal Processing in Smart-X Technologies
提出日: 2021-03-29

The pervasive use of sensors, portable or worn by the user and incorporated in the surrounding environment, generates increasingly large and diversified data flows, big sensor data, which are ill suited to be processed using only traditional signal processing techniques. The application of machine learning in the signal and image processing area has proven very useful in addressing this growing complexity. The systematic use of machine learning and artificial intelligence, with particular focus on the emerging areas of autoML (automatic machine learning) and deep learning (deep artificial neural networks), is receiving much attention in industry and academia for modeling, design, and development of smart technological solutions. In this context, intelligent sensing and advanced signal processing techniques, well suited to treat a large amount of multi-sensor and multi-channel data, generated at a constant rate by the ever-growing number of permanently connected smart devices (according to the Internet of Things paradigm), are the main focus of this Special Issue, aiming at the same time to highlight their great impact in different smart-x sectors, such as smart home, smart building, smart city, smart healthcare, smart transportation, and smart industry, just to name a few. The purpose of this Special Issue is to reflect the most recent advances, present representative applications, and define future research directions related to the application of AI for intelligent sensing and advanced signal processing in smart-x technology, through machine learning, deep learning, computational intelligence, cognitive computing, and other emerging areas of AI. Prospective authors are invited to submit original and high-quality papers that are related, but not limited, to one or more of the following topics: Machine learning techniques for multi-sensor time series analysis, classification, clustering, and forecasting in smart-x applications; Pattern recognition and predictions using multi-sensor time series data; Multi-sensor fusion strategies and their application in smart-x areas; Synthetic long-term multi-sensor time series simulation and generation; Change point detection in multi-sensor time series data; Intelligent sensing-based decision support system for diagnosis, maintenance planning, and operation scheduling in smart-x applications; Machine learning-based critical event detection, diagnosis, and prediction using multi-sensor time series signals; Long-term multi-sensor time series signal processing. Dr. Giovanni Diraco Guest Editor Manuscript Submission Information Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AI is an international peer-reviewed open access quarterly journal published by MDPI. Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions. Keywords multi-sensor time series abnormal event detection and prediction anomaly detection and prediction time series classification time series clustering long-term time series forecasting change point detection decision support systems decision-making techniques synthetic multi-sensor time series long-term multi-sensor time series signal processing predictive analytics predictive maintenance hazard detection/prediction machining monitoring structural health monitoring personal health monitoring
最終更新 Dou Sun 2020-05-07
関連仕訳帳
CCF完全な名前インパクト ・ ファクター出版社ISSN
Wireless Personal Communications0.929Springer0929-6212
aJournal of the ACM ACM0004-5411
SIMULATION1.455SAGE0037-5497
Advances in Data Analysis and Classification1.382Springer1862-5347
ReCALL1.361Cambridge University Press0958-3440
IEEE Access4.098IEEE2169-3536
Journal of ImagingMDPI2313-433X
cActa Informatica0.809Springer0001-5903
AI Communications0.837IOS Press0921-7126
International Journal of Biomedical ImagingHindawi1687-4188
完全な名前インパクト ・ ファクター出版社
Wireless Personal Communications0.929Springer
Journal of the ACM ACM
SIMULATION1.455SAGE
Advances in Data Analysis and Classification1.382Springer
ReCALL1.361Cambridge University Press
IEEE Access4.098IEEE
Journal of ImagingMDPI
Acta Informatica0.809Springer
AI Communications0.837IOS Press
International Journal of Biomedical ImagingHindawi
関連会議
CCFCOREQUALIS省略名完全な名前提出日通知日会議日
CHEMEInternational Conference on Chemical Engineering2020-02-292020-03-302020-06-20
caa1IROSInternational Conference on Intelligent Robots and Systems2020-03-01 2020-10-25
AMIMAInternational Conference on Advanced Materials, Intelligent Manufacturing and Automation2020-04-12 2020-05-15
CyberCInternational Conference on Network-based Distributed Computing and Knowledge Discovery2020-08-102020-09-102020-10-29
ICMNPEnternational Conference on MEMS, Nanotechnology and Precision Engineering2019-02-282019-02-282019-04-26
QCAVQuality Control by Artificial Vision2018-11-012018-12-192019-05-15
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