ICMLC 2026 will be held in Nanjing, China on February 06-09, 2026. The ICMLC 2026 organizing committees invite you to submit the papers to special session. Each special session will be arranged for around 2 hours on Feb. 07 or 08's afternoon. Now the information on special session as following:

Topic: Advances in Computer Vision: Reliability, Explainability, and Real-World Applications

Organizers | 组织者

 

Scope of the Special Session:

This special session welcomes original research contributions, comprehensive surveys, and innovative case studies that address the development of reliable and explainable computer vision systems for real-world applications. We particularly encourage interdisciplinary work that combines core computer vision techniques with interpretability, uncertainty quantification, and deployment-focused reliability.

Introduction: Computer vision has become a cornerstone of modern artificial intelligence, enabling transformative progress in fields ranging from medical imaging and healthcare diagnostics to surveillance, robotics, autonomous driving, and industrial automation. As computer vision systems are increasingly deployed in high-stakes, real-world environments, the need for reliable and explainable models has never been more critical. Beyond achieving state-of-the-art accuracy, today’s research must ensure that models behave consistently under uncertainty, provide transparent reasoning, and support trustworthy decision-making in safety-sensitive domains.
This special session aims to bring together researchers and practitioners working on the next generation of reliable and explainable computer vision methods. By uniting advances in model interpretability, uncertainty quantification, robustness under distribution shift, and domain-specific applications, the session will foster discussion on how to build trustworthy vision systems that bridge the gap between academic innovation and practical deployment. Contributions highlighting applications in medical imaging, surveillance and video analytics, multimodal perception, and other real-world domains are especially welcome.

Topics of interest include, but are not limited to:

Reliable and explainable deep learning architectures for image, video, and multimodal data

Uncertainty quantification, calibration, and confidence estimation in computer vision models

Interpretable computer vision and natural language processing for medical imaging, surveillance, video analytics, and autonomous systems

Robustness under distribution shifts, adversarial perturbations, and noisy real-world data

Trustworthy reinforcement learning and decision-making for visual environments

Causal reasoning and counterfactual explanations in vision-based systems

Human–AI interaction design and visual explanation interfaces for end-users

Bias detection, fairness assessment, and mitigation in multimodal and visual recognition systems

Model compression and efficient computer vision architectures for explainable AI on edge and resource-constrained devices

Federated learning with explainability and privacy-preserving mechanisms

Benchmarking, reproducibility, evaluation metrics, and validation frameworks for explainable computer vision and multimodal AI

Regulatory compliance and ethical frameworks for transparent and explainable vision system deployment

Spatio-temporal data analysis, including video understanding, surveillance, activity recognition, and multimodal temporal fusion

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Welcome to submit more proposal on ICMLC 2026 special session, please download:
 Proposals Submission Guidelines.

Learn more details or submit the proposal, please contact us:
Ms. Doris Ge
Email: icmlc@vip.126.com
Tel: +86-13709044746