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ICMV 2026: International Conference on Machine Vision

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投稿締切日:
2026-07-20 Extended
通知日:
2026-08-10
開催日:
2026-10-15
開催地:
Budapest, Hungary
開催回数:
19
ICORE: C   閲覧: 22264   フォロー: 11   参加: 4

論文募集

ICMV 2026 (International Conference on Machine Vision) is a ICORE C conference held in Budapest, Hungary on 2026-10-15. The paper submission deadline is 2026-07-20 (extended). Acceptance notifications are sent on 2026-08-10.

The theoretical bases of Machine Vision provide the groundwork for developing algorithms and systems that can analyze and interpret visual data effectively. The theoretical bases of machine vision include several key concepts and principles like: Image Formation: Understanding how images are captured through sensors, including concepts like perspective projection, lens optics, and lighting conditions. Image Processing: Techniques for enhancing and manipulating images, such as filtering, noise reduction, histogram equalization, and edge detection. Feature Extraction: Methods to identify and quantify relevant features in images, including geometric shapes, textures, and colors, using techniques like contour detection and SIFT (Scale-Invariant Feature Transform). Pattern Recognition: Algorithms that classify and identify objects or patterns within images, often using machine learning methods like neural networks, support vector machines, or decision trees. Deep learning/Neural networks: Neural networks are computational models inspired by the human brain, designed to recognize patterns and learn from data. Neural networks learn through a process called training, where they adjust their weights based on the error of their predictions using algorithms like backpropagation. Computer Vision Algorithms: Fundamental algorithms for tasks such as object detection, segmentation, and tracking, including deep learning approaches like convolutional neural networks (CNNs). 3D Reconstruction: Techniques to infer three-dimensional structures from two-dimensional images, involving concepts like stereo vision and depth estimation. Geometric Transformations: Theoretical foundations for manipulating image coordinates, including translation, rotation, scaling, and perspective transformations. Machine/Deep Learning: Theoretical underpinnings of supervised, unsupervised, and reinforcement learning, which are used to train models for various vision tasks. Human Vision Models: Insights from biology and psychology that inform how machines can mimic human visual perception, including color theory and visual attention mechanisms. Machine vision fields in their essence leverage advanced technologies that enhance efficiency, accuracy, and decision-making across various sectors. Machine vision encompasses several fields and applications, including: Industrial Automation: Used for quality control, inspection, and monitoring in manufacturing processes. Medical Imaging: Assists in diagnostics and surgical procedures through image analysis and interpretation. Robotics: Enables robots to perceive and interact with their environment, facilitating tasks like object recognition and navigation. Autonomous Vehicles: Critical for obstacle detection, navigation, and traffic sign recognition in self-driving cars. Agricultural Technology: Used in precision farming for crop monitoring, pest detection, and yield estimation. Surveillance and Security: Enhances security systems through facial recognition, anomaly detection, and real-time monitoring. Augmented and Virtual Reality: Supports real-time image processing for immersive experiences and object recognition. Retail and E-commerce: Facilitates automated checkout processes, inventory management, and customer behavior analysis. Sports Analytics: Used for performance analysis, tracking player movements, and improving coaching strategies. Environmental Monitoring: Assists in tracking wildlife, monitoring ecosystems, and assessing environmental changes.
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CCFICORE略称正式名称投稿締切通知日開催日
CMSNInternational Conference on Mobility, Sensing and Networking2026-08-202026-10-162026-12-18
CBWCNCIEEE Wireless Communications and Networking Conference2026-09-152027-04-05
AA*AAAIAAAI Conference on Artificial Intelligence2026-07-212026-11-302027-02-16
CBMMMInternational Conference on MultiMedia Modeling2026-08-162026-10-162027-01-05
CCGPCInternational Conference on Green, Pervasive and Cloud Computing2026-08-012026-09-152026-12-04
CINSCRYPTInternational Conference on Information Security and Cryptology2026-07-082026-08-152026-11-07
CSETTASymposium on Dependable Software Engineering: Theories, Tools and Applications2026-08-102026-09-302026-12-02
CCMMAsiaACM Multimedia Asia2026-08-032026-10-022026-12-15

関連会議

CCFICORE略称正式名称投稿締切通知日開催日
AA*SIGIRInternational Conference on Research and Development in Information Retrieval2026-01-152026-04-022026-07-20
AA*AAAIAAAI Conference on Artificial Intelligence2026-07-212026-11-302027-02-16
AA*CVPRIEEE Conference on Computer Vision and Pattern Recognition2025-11-062026-02-202026-06-03
BA*ICRAInternational Conference on Robotics and Automation2027-05-24
BA*IJCAIInternational Joint Conference on Artificial Intelligence2026-01-312026-08-15
AA*STOCACM Symposium on Theory of Computing2025-11-042026-02-012026-06-22
CICCInternational Conference on Communications2026-10-022027-01-152027-05-30
CBIJCNNInternational Joint Conference on Neural Networks2027-01-312027-03-152027-06-14
BICASSPInternational Conference on Acoustics, Speech and Signal Processing2026-09-162027-01-132027-05-16
BA*PODSACM SIGMOD Conference on Principles of DB Systems2026-12-032027-03-012027-06-13

関連ジャーナル

CCF正式名称インパクトファクター出版社ISSN
CMachine Vision and Applications2.3Springer0932-8092
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
CPattern Recognition Letters3.9Elsevier0167-8655
BPattern Recognition7.6Elsevier0031-3203
IEEE Access3.6IEEE2169-3536

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