HisynSeg: Weakly-Supervised Histopathological Image Segmentation via Image-Mixing Synthesis and Consistency Regularization.

Tissue semantic segmentation is one of the key tasks in computational pathology. To avoid the expensive and laborious acquisition of pixel-level annotations, a wide range of studies attempt to adopt the class activation map (CAM), a weakly-supervised learning scheme, to achieve pixel-level tissue segmentation. However, CAM-based methods are prone to suffer from under-activation and over-activation issues, leading to poor segmentation performance.

Enhancement noise margin and delay time performance of novel punch-through nMOS for single-carrier CMOS.

In this paper, we propose the use of punch-through nMOS (PTnMOS) as an alternative to pMOS in complementary metal oxide semiconductor (CMOS) circuits. According to the TCAD simulation results, PTnMOS exhibit sub-threshold characteristics similar to those of pMOS and can be formed by simply changing the doping concentration of the source and drain. Without the need for sizing, which solves the area occupation problem caused by the need to increase the width of pMOS due to insufficient hole mobility.