Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Xuewen Ding"'
Autor:
Sheng Yang, Leilei Li, Jingbin Liu, Qusen Chen, Xuewen Ding, Hongxing Sun, Yu Wu, Chunhua Ren, Ning Hu
Publikováno v:
Sensors, Vol 19, Iss 3, p 502 (2019)
Cycle slip (CS) is a primary error source in Precise Point Positioning/Inertial Navigation System (PPP/INS) integrated systems. In this study, an INS-aided CS detection and repair method is presented. It utilizes high-precision INS information instea
Externí odkaz:
https://doaj.org/article/0bb06768d6fd4163bc66c120a17fcc34
Autor:
Ziyi Zhang, Xuewen Ding
Publikováno v:
Frontiers in Computing and Intelligent Systems. 2:83-85
YOLOv5s is the network with the smallest depth and feature map width and the fastest image inference, but when applied to small pedestrian target detection in complex scenes, the detection still suffers from wrong and missed detections. To address th
Autor:
Xinnan Cai, Xuewen Ding
Publikováno v:
2023 IEEE 3rd International Conference on Power, Electronics and Computer Applications (ICPECA).
Autor:
Limei Chang, Xuewen Ding
Publikováno v:
2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE).
Autor:
Panpan Sun, Xuewen Ding
Publikováno v:
2022 IEEE 5th International Conference on Information Systems and Computer Aided Education (ICISCAE).
Publikováno v:
2022 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI).
Autor:
Yanli, Chen, Yanqun, Ma, Yanzhi, Zhai, Haiyan, Yang, Chunlan, Zhang, Yingxin, Lu, Wei, Wei, Qing, Cai, Xuewen, Ding, Shan, Lu, Ziyu, Fang
Publikováno v:
Annals of Translational Medicine. 10:1175-1175
Endometriosis is a chronic condition that affects women of child-bearing age. Since the etiology and pathogenesis of endometriosis have not been fully elucidated, it is important to investigate the mechanisms that lead to the deterioration of endomet
Autor:
Chunning Huang, Huaqian Wu, Xuewen Ding, Sikao Wu, Ying Kong, Yuanyuan Liang, Hong Chen, Xianxian Nong, Sanam Acharya
Publikováno v:
Gynecologic oncology. 163(2)
OBJECTIVES The aim of this study was to characterize cervical microbiome feature of reproductive-age women in the progression of squamous intraepithelial lesions (SIL) to cervical cancer. METHODS We characterized the 16S rDNA cervical mucus microbiom
Publikováno v:
2020 IEEE 5th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA).
According to recent results, the support vector machine (SVM) classifiers have excellent facial recognition accuracy in the pattern recognition compare to other classification methods. Moreover, this method provides high performance in generalization
Publikováno v:
ITM Web of Conferences. 45:01011
Face detection places an important role in face recognition which is a popular choice for biometric systems. To solve the low face detection rate problem of face detection in constrained scenario, an efficient face detection method based on migration