CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

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

Late fusion of machine learning models using passively captured interpersonal social interactions and motion from smartphones predicts decompensation in heart failure

Autor: Cakmak, Ayse S., Densen, Samuel, Najarro, Gabriel, Rout, Pratik, Rozell, Christopher J., Inan, Omer T., Shah, Amit J., Clifford, Gari D.

Objective: Worldwide, heart failure (HF) is a major cause of morbidity and mortality and one of the leading causes of hospitalization. Early detection of HF symptoms and pro-active management may reduce adverse events. Approach: Twenty-eight particip

Externí odkaz: http://arxiv.org/abs/2104.01511

AIM 2020: Scene Relighting and Illumination Estimation Challenge

Autor: Helou, Majed El, Zhou, Ruofan, Süsstrunk, Sabine, Timofte, Radu, Afifi, Mahmoud, Brown, Michael S., Xu, Kele, Cai, Hengxing, Liu, Yuzhong, Wang, Li-Wen, Liu, Zhi-Song, Li, Chu-Tak, Das, Sourya Dipta, Shah, Nisarg A., Jassal, Akashdeep, Zhao, Tongtong, Zhao, Shanshan, Nathan, Sabari, Beham, M. Parisa, Suganya, R., Wang, Qing, Hu, Zhongyun, Huang, Xin, Li, Yaning, Suin, Maitreya, Purohit, Kuldeep, Rajagopalan, A. N., Puthussery, Densen, S, Hrishikesh P, Kuriakose, Melvin, C V, Jiji, Zhu, Yu, Dong, Liping, Jiang, Zhuolong, Li, Chenghua, Leng, Cong, Cheng, Jian

We review the AIM 2020 challenge on virtual image relighting and illumination estimation. This paper presents the novel VIDIT dataset used in the challenge and the different proposed solutions and final evaluation results over the 3 challenge tracks.

Externí odkaz: http://arxiv.org/abs/2009.12798

AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results

Autor: Zhang, Kai, Danelljan, Martin, Li, Yawei, Timofte, Radu, Liu, Jie, Tang, Jie, Wu, Gangshan, Zhu, Yu, He, Xiangyu, Xu, Wenjie, Li, Chenghua, Leng, Cong, Cheng, Jian, Wu, Guangyang, Wang, Wenyi, Liu, Xiaohong, Zhao, Hengyuan, Kong, Xiangtao, He, Jingwen, Qiao, Yu, Dong, Chao, Luo, Xiaotong, Chen, Liang, Zhang, Jiangtao, Suin, Maitreya, Purohit, Kuldeep, Rajagopalan, A. N., Li, Xiaochuan, Lang, Zhiqiang, Nie, Jiangtao, Wei, Wei, Zhang, Lei, Muqeet, Abdul, Hwang, Jiwon, Yang, Subin, Kang, JungHeum, Bae, Sung-Ho, Kim, Yongwoo, Qu, Yanyun, Jeon, Geun-Woo, Choi, Jun-Ho, Kim, Jun-Hyuk, Lee, Jong-Seok, Marty, Steven, Marty, Eric, Xiong, Dongliang, Chen, Siang, Zha, Lin, Jiang, Jiande, Gao, Xinbo, Lu, Wen, Wang, Haicheng, Bhaskara, Vineeth, Levinshtein, Alex, Tsogkas, Stavros, Jepson, Allan, Kong, Xiangzhen, Zhao, Tongtong, Zhao, Shanshan, S, Hrishikesh P, Puthussery, Densen, C V, Jiji, Nan, Nan, Liu, Shuai, Cai, Jie, Meng, Zibo, Ding, Jiaming, Ho, Chiu Man, Wang, Xuehui, Yan, Qiong, Zhao, Yuzhi, Chen, Long, Sun, Long, Wang, Wenhao, Liu, Zhenbing, Lan, Rushi, Umer, Rao Muhammad, Micheloni, Christian

This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The challenge task was to super-resolve an input image with a magnification factor x4 based on a set of prior examp

Externí odkaz: http://arxiv.org/abs/2009.06943

AIM 2020 Challenge on Video Extreme Super-Resolution: Methods and Results

Autor: Fuoli, Dario, Huang, Zhiwu, Gu, Shuhang, Timofte, Radu, Raventos, Arnau, Esfandiari, Aryan, Karout, Salah, Xu, Xuan, Li, Xin, Xiong, Xin, Wang, Jinge, Michelini, Pablo Navarrete, Zhang, Wenhao, Zhang, Dongyang, Zhu, Hanwei, Xia, Dan, Chen, Haoyu, Gu, Jinjin, Zhang, Zhi, Zhao, Tongtong, Zhao, Shanshan, Akita, Kazutoshi, Ukita, Norimichi, S, Hrishikesh P, Puthussery, Densen, C V, Jiji

This paper reviews the video extreme super-resolution challenge associated with the AIM 2020 workshop at ECCV 2020. Common scaling factors for learned video super-resolution (VSR) do not go beyond factor 4. Missing information can be restored well in

Externí odkaz: http://arxiv.org/abs/2009.06290