CIR 2025 is a grand gathering of the world's leading scholars and industry experts, scheduled to be held majestically in the scenic city of Guangzhou, China from July 25th to 27th, 2025.
The conference centers on the cutting-edge fields of computing intelligence and robotics, aiming to explore the latest research outcomes, facilitate technological exchanges, strengthen international cooperation, and propel innovation and development in related domains.During the conference, attendees will delve into in-depth discussions surrounding core algorithms of computing intelligence, application cases, as well as the latest advancements in robotics technology, including but not limited to machine learning, deep learning, natural language processing, computer vision, human-robot interaction, service robots, industrial automation, among others. Through keynote speeches, themed forums, technical exhibitions, and paper presentations, CIR 2025 provides participants with an international platform to showcase research findings, broaden academic horizons, and establish cooperative networks.Choosing Guangzhou as the venue not only capitalizes on its strength as an economic and technological innovation hub in southern China but also leverages its open and inclusive urban atmosphere and rich cultural heritage. This selection fosters a conducive environment for interdisciplinary collaboration across the global computing intelligence and robotics landscape. The conference's organization holds significant implications for accelerating technological innovations, addressing real-world challenges, guiding future technological trends, and infusing fresh vitality into Guangzhou's and China's innovation ecosystem.In this regard, we warmly invite researchers, engineers, scholars, and industry leaders worldwide to join this momentous event, collectively propelling computing intelligence and robotics technologies to new heights and ushering in a new chapter in smart technology.
Sponsor Type:3; 9
Machine Learning
· Deep Reinforcement Learning
· Unsupervised Learning
· Transfer Learning
· Meta-Learning
· Generative Adversarial Networks (GAN)
Computer Vision
· Visual Object Tracking
· 3D Visual Reconstruction
· Scene Understanding
· Visual Navigation and Localization
· Visual Recognition in Human-Robot Interaction
Reinforcement Learning
· Autonomous Navigation for Robots
· Multi-Agent Cooperative Reinforcement Learning
· Offline Reinforcement Learning
· Learning in Sparse Reward Environments
· Model-Based Reinforcement Learning
Human-Robot Interaction and Collaboration
· Robot Emotion Recognition
· Verbal and Nonverbal Interaction
· Task Allocation for Collaborative Robots
· Interaction Interface Design
· Socially Adaptable Robots
Data Science and Knowledge Discovery
· Performance Analysis and Optimization for Robots
· Sensor Data Processing and Fusion
· Online Learning and Model Updating
· Data-Driven Fault Detection and Diagnosis
· Applications of Deep Learning in Data Mining
07月25日
2025
07月27日
2025
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