Comprehensive mining of information in Weakly Supervised Semantic Segmentation: Saliency semantics and edge semantics.

In the studies of Weakly Supervised Semantic Segmentation (WSSS) with image-level labels, there is an issue of incomplete semantic information, which we summarize as insufficient saliency semantic mining and neglected edge semantics. We proposes a two-stage framework, Saliency Semantic Full Mining-Edge Semantic Mining (SSFM-ESM), which views WSSS from the perspective of comprehensive information mining. In the first stage, we rely on SSFM to address the insufficient saliency semantic mining. The network learns feature representations consistent with salient regions via the proposed pixel-level class-agnostic distance loss. Then, the full saliency semantic information is mined by explicitly receiving pixel-level feedback. The initial pseudo-label with complete saliency semantic information can be obtained after the first stage. In the second stage, we focus on the mining of edge semantic information through the proposed edge semantic mining module. Specifically, we guide the initial pseudo-label avoid learning about false semantic information and obtain high-confidence edge semantics. The self-correction ability of the segmentation network is also fully utilized to obtain more edge semantic information. Extensive experiments are conducted on the PASCAL VOC 2012 and MS COCO 2014 datasets to verify the feasibility and superiority of this approach.

Study on Magnetic Control Systems of Micro-Robots.

Magnetic control systems of micro-robots have recently blossomed as one of the most thrilling areas in the field of medical treatment. For the sake of learning how to apply relevant technologies in medical services, we systematically review pioneering works published in the past and divide magnetic control systems into three categories: stationary electromagnet control systems, permanent magnet control systems and mobile electromagnet control systems. Based on this, we ulteriorly analyze and illustrate their respective strengths and weaknesses. Furthermore, aiming at surmounting the instability of magnetic control system, we utilize SolidWorks2020 software to partially modify the SAMM system to make its final overall thickness attain 111 mm, which is capable to control and observe the motion of the micro-robot under the microscope system in an even better fashion. Ultimately, we emphasize the challenges and open problems that urgently need to be settled, and summarize the direction of development in this field, which plays a momentous role in the wide and safe application of magnetic control systems of micro-robots in clinic.