With the rapid development of artificial intelligence, deep learning has emerged as a transformative force in image analysis and computer vision, revolutionizing fields such as healthcare, remote sensing, autonomous driving, and digital content creation. Traditional computer vision techniques have been increasingly replaced or augmented by deep learning models, enabling unprecedented accuracy, efficiency, and automation in tasks like image classification, object detection, segmentation, and image generation.

However, despite significant progress, many challenges remain, including the need for large labeled datasets, the interpretability of deep learning models, and the ability to generalize across different domains. Moreover, emerging technologies such as generative adversarial networks (GANs), vision transformers (ViTs), and diffusion models are reshaping the landscape of computer vision, opening new research directions and applications.

This workshop, part of the 2025 3rd International Conference on Data Analysis and Machine Learning (DAML 2025), aims to bring together researchers, industry experts, and practitioners to discuss the latest advancements, challenges, and future trends in deep learning for image analysis. The event will feature keynote talks, research presentations, and interactive discussions, fostering collaboration and innovation in this dynamic field.

We invite researchers and professionals from academia and industry to participate, share their insights, and explore new opportunities in deep learning-driven image analysis and computer vision.