Zobrazeno 1 - 10
of 302
pro vyhledávání: '"Zengchang Qin"'
Autor:
Zengchang Qin, Serik Tabarak, Heng-Yong Guan, Xiang Yang Zhang, Su-Xia Li, Ke-Qiang Wang, Shunyu Zhang, Yuan Chai, Ying-Nan Chen, Xiu-Ru Su, Yan-Xin Lu, Xiao-Yan Li, Hong-Mei Chen, Long Zhao, Shu-Lan Lu
Publikováno v:
Journal of Affective Disorders. 295:264-270
Background Major depressive disorder (MDD) is the most common mental disorder associated with suicide attempts. When a patient first visits the clinic, clinicians are often expected to make concrete diagnose about acute suicidal risk. However, the ti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c717da90a4d7b7cddd30b235feff7b78
https://doi.org/10.1016/j.jad.2021.08.028
https://doi.org/10.1016/j.jad.2021.08.028
Publikováno v:
Journal of Magnetic Resonance Imaging. 55:1491-1503
BACKGROUND Preoperative assessment of the consistency of pituitary macroadenomas (PMA) might be needed for surgical planning. PURPOSE To investigate the diagnostic performance of radiomics models based on multiparametric magnetic resonance imaging (m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f0c837b9884392499ef288fcc5e0c8d1
https://doi.org/10.1002/jmri.27930
https://doi.org/10.1002/jmri.27930
Autor:
Li Dai, Rongyong Zhang, Suyuan Huang, Junyi Liu, Qi Li, Zhen Zhang, Xinshu Jiang, Zengchang Qin
Publikováno v:
2022 14th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::acfc33008a79696af48701da1095ad69
https://doi.org/10.1109/ihmsc55436.2022.00055
https://doi.org/10.1109/ihmsc55436.2022.00055
Publikováno v:
IEEE Transactions on Multimedia. 22:3196-3209
Cross-modal analysis has become a promising direction for artificial intelligence. Visual representation is crucial for various cross-modal analysis tasks that require visual content understanding. Visual features which contain semantical information
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a6e6365dbbfe9660ff9c8e06ec173f24
https://doi.org/10.1109/tmm.2020.2972830
https://doi.org/10.1109/tmm.2020.2972830
Publikováno v:
Neurocomputing. 408:144-156
Automated nuclear segmentation in histopathological images is a prerequisite for a computer-aided diagnosis framework. However, it remains a challenging problem due to the nucleus occlusion or overlapping, shape variation, and image background comple
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c4994efb26a3f2d2b46881e44d36068
https://doi.org/10.1016/j.neucom.2019.08.103
https://doi.org/10.1016/j.neucom.2019.08.103
Publikováno v:
Information Fusion. 55:116-126
The recently emerged research of Visual Question Answering (VQA) has become a hot topic in computer vision. A key solution to VQA exists in how to fuse multimodal features extracted from image and question. In this paper, we show that combining visua
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f09bb725036bf8590c928e9cc684474c
https://doi.org/10.1016/j.inffus.2019.08.009
https://doi.org/10.1016/j.inffus.2019.08.009
Publikováno v:
Pattern Recognition Letters. 130:189-198
Cross-modal information retrieval aims to find heterogeneous data of various modalities from a given query of one modality. The main challenge is to learn the semantic correlations between different modalities and measure the distance across modaliti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::85a3dc996d0d2c2b74f0b196b2ccd909
https://doi.org/10.1016/j.patrec.2018.08.017
https://doi.org/10.1016/j.patrec.2018.08.017
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030980177
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c2a2383d4467c39739a0fc105dbca7e
https://doi.org/10.1007/978-3-030-98018-4_22
https://doi.org/10.1007/978-3-030-98018-4_22
Publikováno v:
Knowledge-Based Systems. 256:109820
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe302f70ede8a3f31fbc9e6c8165dc46
https://doi.org/10.1016/j.knosys.2022.109820
https://doi.org/10.1016/j.knosys.2022.109820
Publikováno v:
Neurocomputing. 365:157-170
Accurate cell segmentation is essential for computer-aided diagnosis of cervical precancerous lesions in cytology images. Automated segmentation poses a great challenge due to the presence of fuzzy and overlapping cells, noisy background, and poor cy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a4682cde428fcb568298760aa6a909e
https://doi.org/10.1016/j.neucom.2019.06.086
https://doi.org/10.1016/j.neucom.2019.06.086