Zobrazeno 1 - 10
of 627
pro vyhledávání: '"Han, Guoqiang"'
Autor:
Lin, Jiatai, Han, Guoqiang, Xu, Xuemiao, Liang, Changhong, Wong, Tien-Tsin, Chen, C. L. Philip, Liu, Zaiyi, Han, Chu
Class activation mapping~(CAM), a visualization technique for interpreting deep learning models, is now commonly used for weakly supervised semantic segmentation~(WSSS) and object localization~(WSOL). It is the weighted aggregation of the feature map
Externí odkaz:
http://arxiv.org/abs/2309.03509
Autor:
Wang, Hao, Lin, Jiatai, Li, Danyi, Wang, Jing, Zhao, Bingchao, Shi, Zhenwei, Pan, Xipeng, Wang, Huadeng, Li, Bingbing, Liang, Changhong, Han, Guoqiang, Liang, Li, Han, Chu, Liu, Zaiyi
Mitosis detection is one of the fundamental tasks in computational pathology, which is extremely challenging due to the heterogeneity of mitotic cell. Most of the current studies solve the heterogeneity in the technical aspect by increasing the model
Externí odkaz:
http://arxiv.org/abs/2307.05889
Autor:
Deng, Tianpeng, Huang, Yanqi, Han, Guoqiang, Shi, Zhenwei, Lin, Jiatai, Dou, Qi, Liu, Zaiyi, Guo, Xiao-jing, Chen, C. L. Philip, Han, Chu
Histopathological tissue classification is a fundamental task in computational pathology. Deep learning-based models have achieved superior performance but centralized training with data centralization suffers from the privacy leakage problem. Federa
Externí odkaz:
http://arxiv.org/abs/2302.12662
Autor:
Lin, Jianwei, Lin, Jiatai, Lu, Cheng, Chen, Hao, Lin, Huan, Zhao, Bingchao, Shi, Zhenwei, Qiu, Bingjiang, Pan, Xipeng, Xu, Zeyan, Huang, Biao, Liang, Changhong, Han, Guoqiang, Liu, Zaiyi, Han, Chu
Brain tumor segmentation (BTS) in magnetic resonance image (MRI) is crucial for brain tumor diagnosis, cancer management and research purposes. With the great success of the ten-year BraTS challenges as well as the advances of CNN and Transformer alg
Externí odkaz:
http://arxiv.org/abs/2207.07370
WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma
Autor:
Han, Chu, Pan, Xipeng, Yan, Lixu, Lin, Huan, Li, Bingbing, Yao, Su, Lv, Shanshan, Shi, Zhenwei, Mai, Jinhai, Lin, Jiatai, Zhao, Bingchao, Xu, Zeyan, Wang, Zhizhen, Wang, Yumeng, Zhang, Yuan, Wang, Huihui, Zhu, Chao, Lin, Chunhui, Mao, Lijian, Wu, Min, Duan, Luwen, Zhu, Jingsong, Hu, Dong, Fang, Zijie, Chen, Yang, Zhang, Yongbing, Li, Yi, Zou, Yiwen, Yu, Yiduo, Li, Xiaomeng, Li, Haiming, Cui, Yanfen, Han, Guoqiang, Xu, Yan, Xu, Jun, Yang, Huihua, Li, Chunming, Liu, Zhenbing, Lu, Cheng, Chen, Xin, Liang, Changhong, Zhang, Qingling, Liu, Zaiyi
Lung cancer is the leading cause of cancer death worldwide, and adenocarcinoma (LUAD) is the most common subtype. Exploiting the potential value of the histopathology images can promote precision medicine in oncology. Tissue segmentation is the basic
Externí odkaz:
http://arxiv.org/abs/2204.06455
Autor:
Lin, Jiatai, Han, Guoqiang, Pan, Xipeng, Chen, Hao, Li, Danyi, Jia, Xiping, Shi, Zhenwei, Wang, Zhizhen, Cui, Yanfen, Li, Haiming, Liang, Changhong, Liang, Li, Liu, Zaiyi, Han, Chu
Histopathological tissue classification is a fundamental task in pathomics cancer research. Precisely differentiating different tissue types is a benefit for the downstream researches, like cancer diagnosis, prognosis and etc. Existing works mostly l
Externí odkaz:
http://arxiv.org/abs/2111.03063
Autor:
Zhao, Shen, Wang, Chunyang, Han, Guoqiang, Liu, Haitao, Xie, Guangwen, Liu, Xin, Jiang, Luhua
Publikováno v:
In Applied Surface Science 30 July 2024 662
Autor:
Han, Chu, Lin, Jiatai, Mai, Jinhai, Wang, Yi, Zhang, Qingling, Zhao, Bingchao, Chen, Xin, Pan, Xipeng, Shi, Zhenwei, Xu, Xiaowei, Yao, Su, Yan, Lixu, Lin, Huan, Xu, Zeyan, Huang, Xiaomei, Han, Guoqiang, Liang, Changhong, Liu, Zaiyi
Tissue-level semantic segmentation is a vital step in computational pathology. Fully-supervised models have already achieved outstanding performance with dense pixel-level annotations. However, drawing such labels on the giga-pixel whole slide images
Externí odkaz:
http://arxiv.org/abs/2110.08048
The fully convolutional network (FCN) has dominated salient object detection for a long period. However, the locality of CNN requires the model deep enough to have a global receptive field and such a deep model always leads to the loss of local detai
Externí odkaz:
http://arxiv.org/abs/2108.02759
Autor:
Yang, Sha, Guo, Jing, Xiong, Yunbiao, Han, Guoqiang, Luo, Tao, Peng, Shuo, Liu, Jian, Hu, Tieyi, Zha, Yan, Lin, Xin, Tan, Ying, Zhang, Jiqin
Publikováno v:
In International Immunopharmacology 20 August 2024 137