Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Kuan-Lun Tseng"'
Autor:
Kuan-Lun Tseng, 曾冠綸
106
Deep learning models such as convolutional neural network have been widely used in 3D biomedical segmentation and achieve state-of-the-art performance. However, most of them often adapt a single modality or stack multiple modalities as diffe
Deep learning models such as convolutional neural network have been widely used in 3D biomedical segmentation and achieve state-of-the-art performance. However, most of them often adapt a single modality or stack multiple modalities as diffe
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/rkmn36
Autor:
Kuan-Lun Tseng, Casper F. Winsnes, Kevin Hwang, Xuan Cao, Martin Hjelmare, Alexander Kiselev, Yuanhao Wu, Gu Yinzheng, Hongdong Zheng, Sergei Fironov, Shaikat M. Galib, Jun Lan, Constantin Kappel, Emma Lundberg, Dmytro Poplavskiy, Anthony J. Cesnik, Wei Ouyang, Xiaohan Yi, Hao Xu, Russel D. Wolfinger, Dmitry Buslov, Devin P. Sullivan, Jinbin Xie, Cheng Ju, Dmytro Panchenko, Zhifeng Gao, Chuanpeng Li, Park Jinmo, Christof Henkel, Runmin Wei, Shubin Dai, Xun Zhu, Bojan Tunguz, Lovisa Åkesson
Publikováno v:
Nature Methods
Pinpointing subcellular protein localizations from microscopy images is easy to the trained eye, but challenging to automate. Based on the Human Protein Atlas image collection, we held a competition to identify deep learning solutions to solve this t
Autor:
Wei Ouyang, Casper F. Winsnes, Martin Hjelmare, Anthony J. Cesnik, Lovisa Åkesson, Hao Xu, Devin P. Sullivan, Shubin Dai, Jun Lan, Park Jinmo, Shaikat M. Galib, Christof Henkel, Kevin Hwang, Dmytro Poplavskiy, Bojan Tunguz, Russel D. Wolfinger, Yinzheng Gu, Chuanpeng Li, Jinbin Xie, Dmitry Buslov, Sergei Fironov, Alexander Kiselev, Dmytro Panchenko, Xuan Cao, Runmin Wei, Yuanhao Wu, Xun Zhu, Kuan-Lun Tseng, Zhifeng Gao, Cheng Ju, Xiaohan Yi, Hongdong Zheng, Constantin Kappel, Emma Lundberg
Publikováno v:
Nature Methods
Pinpointing subcellular protein localizations from microscopy images is easy to the trained eye, but challenging to automate. Based on the Human Protein Atlas image collection, we held a competition to identify deep learning solutions to solve this t
Autor:
Xiaohan Yi, Anthony J. Cesnik, Kuan-Lun Tseng, Runmin Wei, Park Jinmo, Cheng Ju, Emma Lundberg, Shubin Dai, Jun Lan, Zhifeng Gao, Jinbin Xie, Martin Hjelmare, Dmytro Poplavskiy, Yuanhao Wu, Christof Henkel, Casper F. Winsnes, Hongdong Zheng, Devin P. Sullivan, Gu Yinzheng, Kevin Hwang, Russel D. Wolfinger, Wei Ouyang, Alexander Kiselev, Xun Zhu, Bojan Tunguz, Hao Xu, Lovisa Åkesson, Constantin Kappel, Sergei Fironov, Shaikat M. Galib, Dmitry Buslov, Chuanpeng Li, Xuan Cao, Dmytro Panchenko
Publikováno v:
Nature Methods
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Publikováno v:
CVPR
Deep learning models such as convolutional neural net- work have been widely used in 3D biomedical segmentation and achieve state-of-the-art performance. However, most of them often adapt a single modality or stack multiple modalities as different in