Progressive Complementary Knowledge Aggregation for CdZnTe Defect Segmentation-Reference-Cited by-同舟云学术

Progressive Complementary Knowledge Aggregation for CdZnTe Defect Segmentation

Author:

Li Peihao¹,Li Feng²^ORCID,Liu Man¹^ORCID,Bai Huihui¹^ORCID,Wei Yunchao¹^ORCID,Wang Anhong³^ORCID,Ma Shijie⁴,Zhao Yao¹^ORCID

Affiliation:

1. Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing, China

2. School of Computer Science and Information Engineering (School of Artificial Intelligence), Hefei University of Technology, Hefei, China

3. Institute of Digital Media Communication, Taiyuan University of Science and Technology, Taiyuan, China

4. 2nd Research Institute of China Electronics Technology Group Corporation, Beijing, China

Funder

National Natural Science Foundation of China

Beijing Natural Science Foundation

Industrial Vision Application of Shanxi Provincial Technology Innovation Center

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

Reference37 articles.

3. Faster R-CNN: Towards real-time object detection with region proposal networks;Ren,2015

4. CCNet: Criss-cross attention for semantic segmentation;Zilong,2019