Progressive CNN-transformer semantic compensation network for polyp segmentation
Information Sciences|更新时间:2024-09-27
|
Progressive CNN-transformer semantic compensation network for polyp segmentation
“In the field of medical image processing, researchers have proposed a novel progressive CNN Transformer network, which effectively improves the accuracy of colon polyp segmentation and provides a new method for improving diagnostic accuracy.”
Optics and Precision EngineeringVol. 32, Issue 16, Pages: 2523-2536(2024)
LI Daxiang,LI Denghui,LIU Ying,et al.Progressive CNN-transformer semantic compensation network for polyp segmentation[J].Optics and Precision Engineering,2024,32(16):2523-2536.
Cascade residual-optimized image super-resolution reconstruction in Transformer network
Collaborative classification of hyperspectral and LiDAR data based on CNN-transformer
Fast registration of point cloud of complex hollow turbine blade
A Transformer-based visual tracker via knowledge distillation
Secret key extraction from atmospheric wireless optical channels by combing with generative adversarial network
Related Author
LIN Jianpu
WU Zhencheng
WANG Kunfu
LIN Zhixian
GUO Tailiang
LIN Shanling
WU Haibin
DAI Shiyu
Related Institution
School of Advanced Manufacturing,Fuzhou University
Fujian Science and Technology Innovation Laboratory for Optoelectronic Information of China
College of Physics and Telecommunication Engineering, Fuzhou University
Heilongjiang Province Key Laboratory of Laser Spectroscopy Technology and Application, College of Measurement and Control Technology and Communication Engineering, Harbin University of Science and Technology