Intelligent Analysis and Image Recognition

Dear Colleagues,

Major progress is being published regularly on both the technology and exploitation of Intelligent Analysis and Image Recognition. However, the real-world applications of intelligent data analysis and image recognition technologies are still limited. This is related to several factors, such as the complexity of realistic scenes, the high cost of computing resources in large models and the difficulties associated with large amounts of annotated data. Current research is also focusing on the efficient use of multi-domain data. For example, infrared images can compensate for the absence of RGB image information in low-illumination scenes. Different image domains have differentiated target features. It is very important to use the information of different image domains to obtain more powerful image recognition models and build highly robust models for different image domains. We are interested in articles that explore robust intelligent analysis and image recognition systems. Potential topics include, but are not limited to, the following:

• Intelligent recognition of large-scale images;
• Multi-domain image recognition;
• Few-shot/zero-shot image recognition;
• Graph representation of images;
• Multi-view image joint recognition;
• Image recognition based on big data analytics;
• Intelligent image recognition for real-world applications;
• Efficient image recognition systems on embedded devices.

Prof. Dr. Qi Zhao
Dr. Lijiang Chen
Guest Editors

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