Visual Intelligent Recognition System based on Visual Thinking

Abstract

Image semantic segmentation plays an important role and has application value in robot arm object capture, automatic driving, medical image analysis, geographic information system, etc. Aiming at the semantic segmentation method of deep learning(DL), this paper makes some attempts in the direction of weak supervised semantic segmentation, proposes AI and DL technology, and applies them to the Image segmentation technology(IST) in the construction machinery(CM) grasping task for analysis and exploration. The improvement of image weak location based on depth learning, network segmentation graph and image classification objective function are briefly analyzed. Finally, the experimental test analysis shows that a better initial attention map is not only helpful for direct segmentation, but also can promote the joint optimization performance, which verifies the effectiveness and feasibility of IST in the CM grasping task relying on AI and depth learning in this paper.

Design of intelligent agricultural landscape planning and ecological balance control system based on remote sensing images

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