Zobrazeno 1 - 10
of 99
pro vyhledávání: '"Lin, Chunhui"'
Autor:
Tang, Jingqun, Liu, Qi, Ye, Yongjie, Lu, Jinghui, Wei, Shu, Lin, Chunhui, Li, Wanqing, Mahmood, Mohamad Fitri Faiz Bin, Feng, Hao, Zhao, Zhen, Wang, Yanjie, Liu, Yuliang, Liu, Hao, Bai, Xiang, Huang, Can
Text-Centric Visual Question Answering (TEC-VQA) in its proper format not only facilitates human-machine interaction in text-centric visual environments but also serves as a de facto gold proxy to evaluate AI models in the domain of text-centric scen
Externí odkaz:
http://arxiv.org/abs/2405.11985
Autor:
Tang, Jingqun, Lin, Chunhui, Zhao, Zhen, Wei, Shu, Wu, Binghong, Liu, Qi, Feng, Hao, Li, Yang, Wang, Siqi, Liao, Lei, Shi, Wei, Liu, Yuliang, Liu, Hao, Xie, Yuan, Bai, Xiang, Huang, Can
Text-centric visual question answering (VQA) has made great strides with the development of Multimodal Large Language Models (MLLMs), yet open-source models still fall short of leading models like GPT4V and Gemini, partly due to a lack of extensive,
Externí odkaz:
http://arxiv.org/abs/2404.12803
Autor:
Zhao, Zhen, Tang, Jingqun, Lin, Chunhui, Wu, Binghong, Huang, Can, Liu, Hao, Tan, Xin, Zhang, Zhizhong, Xie, Yuan
Scene text recognition (STR) in the wild frequently encounters challenges when coping with domain variations, font diversity, shape deformations, etc. A straightforward solution is performing model fine-tuning tailored to a specific scenario, but it
Externí odkaz:
http://arxiv.org/abs/2311.13120
Autor:
Graham, Simon, Vu, Quoc Dang, Jahanifar, Mostafa, Weigert, Martin, Schmidt, Uwe, Zhang, Wenhua, Zhang, Jun, Yang, Sen, Xiang, Jinxi, Wang, Xiyue, Rumberger, Josef Lorenz, Baumann, Elias, Hirsch, Peter, Liu, Lihao, Hong, Chenyang, Aviles-Rivero, Angelica I., Jain, Ayushi, Ahn, Heeyoung, Hong, Yiyu, Azzuni, Hussam, Xu, Min, Yaqub, Mohammad, Blache, Marie-Claire, Piégu, Benoît, Vernay, Bertrand, Scherr, Tim, Böhland, Moritz, Löffler, Katharina, Li, Jiachen, Ying, Weiqin, Wang, Chixin, Kainmueller, Dagmar, Schönlieb, Carola-Bibiane, Liu, Shuolin, Talsania, Dhairya, Meda, Yughender, Mishra, Prakash, Ridzuan, Muhammad, Neumann, Oliver, Schilling, Marcel P., Reischl, Markus, Mikut, Ralf, Huang, Banban, Chien, Hsiang-Chin, Wang, Ching-Ping, Lee, Chia-Yen, Lin, Hong-Kun, Liu, Zaiyi, Pan, Xipeng, Han, Chu, Cheng, Jijun, Dawood, Muhammad, Deshpande, Srijay, Bashir, Raja Muhammad Saad, Shephard, Adam, Costa, Pedro, Nunes, João D., Campilho, Aurélio, Cardoso, Jaime S., S, Hrishikesh P, Puthussery, Densen, G, Devika R, C V, Jiji, Zhang, Ye, Fang, Zijie, Lin, Zhifan, Zhang, Yongbing, Lin, Chunhui, Zhang, Liukun, Mao, Lijian, Wu, Min, Vo, Vi Thi-Tuong, Kim, Soo-Hyung, Lee, Taebum, Kondo, Satoshi, Kasai, Satoshi, Dumbhare, Pranay, Phuse, Vedant, Dubey, Yash, Jamthikar, Ankush, Vuong, Trinh Thi Le, Kwak, Jin Tae, Ziaei, Dorsa, Jung, Hyun, Miao, Tianyi, Snead, David, Raza, Shan E Ahmed, Minhas, Fayyaz, Rajpoot, Nasir M.
Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovation in this area, we setup a community-wide challenge using the largest
Externí odkaz:
http://arxiv.org/abs/2303.06274
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
Nuclear segmentation, classification and quantification within Haematoxylin & Eosin stained histology images enables the extraction of interpretable cell-based features that can be used in downstream explainable models in computational pathology (CPa
Externí odkaz:
http://arxiv.org/abs/2203.00262
Publikováno v:
UCJC Business & Society Review. 2024 1st Quarter, Issue 80, p260-299. 40p.
Publikováno v:
In Journal of Microbiological Methods August 2023 211
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Akademický článek
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