Conference Information

ISPR 2025: International Conference on Intelligent systems and Pattern Recognition

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Submission Date:
2025-06-30
Notification Date:
2025-07-30
Conference Date:
2025-09-25
Location:
Hammamet, Tunisia
Years:
5
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Call For Papers

ISPR 2025 (International Conference on Intelligent systems and Pattern Recognition) is an academic conference held in Hammamet, Tunisia on 2025-09-25. The paper submission deadline is 2025-06-30. Acceptance notifications are sent on 2025-07-30.

The conference covers a wide array of themes reflecting current trends and emerging challenges in intelligent systems and pattern recognition. Topics include, but are not limited to, the following tracks: Track 1: Artificial Intelligence & Intelligent Systems Natural Language Processing Knowledge Representation and Reasoning Constraint Processing and Heuristic Search Intelligent Interfaces Multi-Agent Systems Machine and Deep Learning Data Mining Fuzzy Logic Systems and Applications Intelligent Decision-Making Systems Genetic Algorithms and Evolutionary Modeling Particle Swarm Optimization and Ant Colony Algorithms Hybrid Systems of Computational Intelligence Knowledge-Based Systems Expert Systems and Decision Support Systems Robotics and Autonomous Systems Reinforcement Learning Cognitive Computing Emotion and Affect Recognition Human-Robot Interaction Explainable AI Computer Vision for Robotics Intelligent Transportation Systems Social and Ethical Issues in AI Track 2: Pattern Recognition Handwriting Document Analysis and Recognition Image Processing Automatic Speech Recognition Signal Processing Video Processing Biometrics Applications Computer Vision, Robotics, and Perception Virtual Reality Medical Image Processing Deep Learning for Pattern Recognition Feature Extraction Techniques Shape Analysis and Recognition Object Detection and Recognition Biomedical Image Analysis Multimodal Pattern Recognition Pattern Recognition for Security and Surveillance Applications Signal and Time Series Analysis Brain-Computer Interfaces Natural Language Understanding Dimensionality Reduction for High-Dimensional Data Analysis Pattern Recognition for IoT Applications
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