New Challenges in Image Processing and Pattern Recognition

Dear Colleagues,

The topic “New Challenges in Image Processing and Pattern Recognition” aims to provide a comprehensive and forward-looking platform for the exchange of innovative research addressing emerging issues, novel methodologies, and multidisciplinary applications in the fields of image processing and pattern recognition. As digital imagery becomes increasingly central across domains—ranging from autonomous systems and biomedical imaging to security, remote sensing, and industrial automation—new challenges continue to arise due to growing data complexity, real-time demands, and the integration of artificial intelligence.

This topic seeks contributions that push the boundaries of current techniques or offer novel perspectives on traditional problems. We welcome both theoretical developments and practical applications that demonstrate clear innovation and impact.

The scope of the topic includes, but is not limited to:

• Advanced image enhancement, restoration, and reconstruction techniques;
• Deep learning architectures and transformer models for image understanding;
• Explainable AI (XAI) and trustworthy pattern recognition systems;
• Real-time and embedded vision systems for edge computing;
• Multimodal data fusion (e.g., RGB-D, thermal, hyperspectral);
• Three-dimensional vision, shape analysis, and object recognition in complex scenes;
• Bio-inspired and physics-informed image analysis models;
• Adversarial attacks, robustness, and secure pattern recognition;
• Image processing in biomedical, environmental, industrial, and artistic domains;
• Benchmarking and evaluation metrics for image processing algorithms.

The topic encourages interdisciplinary approaches and collaborative studies that link computer vision with neuroscience, cognitive science, computational imaging, and other related fields.

Dr. Pei-Ju Chiang
Dr. Cheng-Lun Chen
Dr. Ping-Huan Kuo
Prof. Dr. Wen-Yang Chang
Topic Editors