AI and Data-Driven Advancements in Industry 4.0, 2nd Edition

Dear Colleagues,

Our society is awash with diverse forms of data—pictures, point clouds, text, audio, video, and beyond. Data-driven artificial intelligence offers the potential to extract meaningful insights from this deluge, unlocking extraordinary opportunities in both theory and application. Recent years have witnessed a proliferation of AI theories and algorithms, now trusted and employed across sectors like finance, security, education, art, neuroscience, and even music. Inspired by these advancements, substantial AI-based techniques are being implemented in fields as varied as autonomous driving, virtual reality, human–computer interaction, remote sensing, and artistic creation.

This focus area seeks to collect and highlight the latest breakthroughs in next-generation artificial intelligence and its applications within the context of Industry 4.0. Our interest spans the full spectrum of AI research, from compact on-device models to expansive large-scale models, across diverse domains. We are particularly keen on sophisticated framework designs, training strategies, optimization techniques, and ensuring the trustworthiness and robustness of AI systems, along with their real-world applications.

Topics include (but are not limited to) the following:

• Computer vision, natural language processing, reinforcement learning;
• Large-scale language model, large-scale vision model, prompt learning, retrieval-augmented generation;
• Multi-modal learning, object recognition, detection, segmentation, tracking;
• Graph neural network, knowledge graph, recommendation system;
• Pattern recognition and intelligent system;
• Blockchain theory or application, smart contract;
• Artificial intelligence security, data security and privacy;
• Remote sensing image interpretation;
• Art generation and creation, art analysis and understanding;
• Virtual reality, robotics, edge computing, on-device models;
• Autonomous driving.

Dr. Teng Huang
Dr. Yan Pang
Prof. Dr. Qiong Wang
Prof. Dr. Jianjun Li
Dr. Jin Liu
Dr. Jia Wang
Topic Editors