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ICPRAM 2027: International Conference on Pattern Recognition Applications and Methods

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ICPRAM
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Día de Entrega:
2026-09-15 Faltan 18 días
Fecha de Notificación:
2026-11-13
Fecha de conferencia:
2027-02-20
Ubicación:
Valletta, Malta
Ediciones:
ICORE: C   Vistas: 22065   Seguidores: 8   Asistentes: 0

Solicitud de Artículos

ICPRAM 2027 (International Conference on Pattern Recognition Applications and Methods) is a ICORE C conference held in Valletta, Malta on 2027-02-20. The paper submission deadline is 2026-09-15. Acceptance notifications are sent on 2026-11-13.

SCOPE The International Conference on Pattern Recognition Applications and Methods is a major point of contact between researchers, engineers and practitioners on the areas of Pattern Recognition and Machine Learning, both from theoretical and application perspectives. Contributions describing applications of Pattern Recognition techniques to real-world problems, interdisciplinary research, experimental and/or theoretical studies yielding new insights that advance Pattern Recognition methods are especially encouraged. Papers describing original work are invited in any of the areas listed below. Accepted papers, presented at the conference by one of the authors, will be published in the proceedings of ICPRAM with an ISBN. Acceptance will be based on quality, relevance and originality. There will be both oral and poster sessions. Special sessions, dedicated to case-studies and commercial presentations, as well as technical tutorials, dedicated to technical/scientific topics, are also envisaged: companies interested in presenting their products/methodologies or researchers interested in presenting a demo or lecturing a tutorial are invited to contact the conference secretariat. CONFERENCE AREAS Each of the topic areas is expanded below but the sub-topics list is not exhaustive. Papers may address one or more of the listed sub-topics, although authors should not feel limited by them. Unlisted but related sub-topics are also acceptable, provided they fit in one of the following main topic areas: 1. THEORY AND METHODS 2. APPLICATIONS AREA 1: THEORY AND METHODS Advanced Learning Methods Machine Learning Methods Deep Learning and Neural Networks Model Representation and Selection Classification and Clustering Ensemble Methods Signal Processing Stochastic Methods Feature Extraction, Feature Selection and Dimensionality Reduction Knowledge Acquisition and Representation Data Mining and Algorithms for Big Data AREA 2: APPLICATIONS Audio and Speech Analysis Motion Tracking and Action Recognition Natural Language Processing Pattern Recognition for Robotics Sensors and Early Vision Pattern Recognition in Virtual Environments Bioinformatics and Systems Biology Biometrics Document Analysis Image and Video Analysis and Understanding Industry Related Applications Information Retrieval Medical Imaging Autonoumous Driving Food Recognition Pattern Recognition in Agriculture
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