Zobrazeno 1 - 10
of 84
pro vyhledávání: '"Xiaoliang Qian"'
Autor:
Wei Xu, Liying Zhang, Xiaoliang Qian, Nannan Sun, Xiao Tu, Dengfeng Zhou, Xiaoping Zheng, Jia Chen, Zewen Xie, Tao He, Shugang Qu, Yinjia Wang, Keda Yang, Kunkai Su, Shan Feng, Bin Ju
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Clinical proteomics analysis is of great significance for analyzing pathological mechanisms and discovering disease-related biomarkers. Using computational methods to accurately predict disease types can effectively improve patient disease d
Externí odkaz:
https://doaj.org/article/538a96d15c07400b96344a115d2c6e01
Publikováno v:
ACS Omega, Vol 9, Iss 22, Pp 23940-23948 (2024)
Externí odkaz:
https://doaj.org/article/cb166998e3f145439e9a9ad2aad9339d
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-11 (2023)
Abstract The segmentation and extraction on color features can provide useful information for many different application domains. However, most of the existing image processing algorithms on feature extraction are gray image-based and consider only o
Externí odkaz:
https://doaj.org/article/caab8d97242945599e3c3e1e62200a4c
Publikováno v:
Frontiers in Neurorobotics, Vol 18 (2024)
The tactile object recognition (TOR) is highly important for environmental perception of robots. The previous works usually utilize single scale convolution which cannot simultaneously extract local and global spatiotemporal features of tactile data,
Externí odkaz:
https://doaj.org/article/22c613cea81f4c6b82a0ee824f0c1d0a
Publikováno v:
Mathematics, Vol 12, Iss 9, p 1343 (2024)
Oriented object detection (OOD) can precisely detect objects with arbitrary direction in remote sensing images (RSIs). Up to now, the two-stage OOD methods have attracted more attention because of their high detection accuracy. However, the two-stage
Externí odkaz:
https://doaj.org/article/e17a1a293fc841199dec441fa37b860a
Publikováno v:
Remote Sensing, Vol 16, Iss 9, p 1532 (2024)
Weakly supervised object detection (WSOD) in remote sensing images (RSIs) aims to detect high-value targets by solely utilizing image-level category labels; however, two problems have not been well addressed by existing methods. Firstly, the seed ins
Externí odkaz:
https://doaj.org/article/0727c95bbd8d4b84a5934db92981e50d
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 7497-7506 (2023)
Weakly supervised object detection (WSOD) has a great practical value in remote sensing image (RSI) interpretation because the instance-level annotations are not required. The multiple instance learning based methods are mainstream, and two problems
Externí odkaz:
https://doaj.org/article/382294daf0504b12aa76df95d4953235
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 119, Iss , Pp 103301- (2023)
Weakly supervised object detection (WSOD) in remote sensing images (RSIs) has good practical value because it only requires the image-level annotations. The existing methods usually have two problems. The first problem is that many methods mine the p
Externí odkaz:
https://doaj.org/article/6be951de09bf4850844dfaed43e02c7d
Publikováno v:
Frontiers in Neurorobotics, Vol 17 (2023)
Tactile object recognition (TOR) is very important for the accurate perception of robots. Most of the TOR methods usually adopt uniform sampling strategy to randomly select tactile frames from a sequence of frames, which will lead to a dilemma proble
Externí odkaz:
https://doaj.org/article/abd8aa3158a84748b75984132fb950f7
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 1902-1911 (2022)
Weakly supervised object detection (WSOD) in remote sensing images (RSI) only require image-level labels to detect various objects. Most of the WSOD methods incline to capture the most discriminative parts of object rather than the entire object, and
Externí odkaz:
https://doaj.org/article/935234cb9ea146a39392d2aa7c64f7cf