Intelligent Robotic Visual Perception with Deep Learning provides an in-depth exploration of deep learning-based robot Intelligent vision perception technologies that helps readers establish a solid foundation to learn about the applications and latest theoretical methods in visual perception. The book, in a comprehensive manner, covers the research aspects of deep learning technology in intelligent visual perception, ranging from methods to practical applications, algorithm analysis, and model construction. Users will find the latest international research trends that are essential for researchers working in the area.
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Dr. Qiaokang Liang is a Professor at the College of Electrical and Information Engineering, Hunan University, China. He also serves as the Deputy Director of the National Engineering Research Center for Robot Vision Perception and Control. His research interests include robotics and mechatronics, biomimetic sensing, advanced robot technology, and human–computer interaction
Hai Qin is a Ph.D. candidate at the College of Electrical and Information Engineering, Hunan University, China, and a research member at the National Engineering Research Center for Robot Vision Perception and Control. His research interests encompass intelligent robotic perception, computer vision, and machine learning
Shao Xiang is a researcher based at the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China; Shao Xiang is also a member of the National Engineering Research Center for Robot Vision Perception and Control.
His research interests include change detection of remote sensing, image compression, object detection and semantic segmentation
Intelligent Robotic Visual Perception with Deep Learning provides an in-depth exploration of deep learning-based robot Intelligent vision perception technology, establishing a solid foundation for engineering professionals to learn about the applications and latest theoretical methods in visual perception. The book, in a comprehensive manner, covers the research aspects of deep learning technology in intelligent visual perception, ranging from methods to practical applications, algorithm analysis to model construction. It integrates the latest international research trends, providing an essential reference for researchers working in the area.
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