Intelligent Robotic Visual Perception With Deep Learning

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

• 1. An overview of the development and challenges of robot vision perception systems2. The components, main implementation steps, and typical applications of robot vision perception systems3. D deep learning technologies in robot vision perception systems4. Text detection based on image segmentation and sequence-based scene text recognition technologies in natural scenes5. Visual object detection technologies, with a focus on R-FCN-based and Mask RCNN-based object detection methods6. Multi-object tracking technologies, emphasizing sequence feature-based and context graph model-based multi-object tracking methods7. Image segmentation methods, with a focus on remote sensing image semantic segmentation using adaptive feature selection networks and region segmentation based on SU-SWA