Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Zudi Lin"'
Autor:
Xiaomeng Han, Xiaotang Lu, Peter H. Li, Shuohong Wang, Richard Schalek, Yaron Meirovitch, Zudi Lin, Jason Adhinarta, Karl D. Murray, Leah M. MacNiven, Daniel R. Berger, Yuelong Wu, Tao Fang, Elif Sevde Meral, Shadnan Asraf, Hidde Ploegh, Hanspeter Pfister, Donglai Wei, Viren Jain, James S. Trimmer, Jeff W. Lichtman
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-18 (2024)
Abstract Mapping neuronal networks is a central focus in neuroscience. While volume electron microscopy (vEM) can reveal the fine structure of neuronal networks (connectomics), it does not provide molecular information to identify cell types or funct
Externí odkaz:
https://doaj.org/article/af6d34c529a5478a859e10bc1f1a99bb
Autor:
Leander Lauenburg, Zudi Lin, Ruihan Zhang, Márcia dos Santos, Siyu Huang, Ignacio Arganda-Carreras, Edward S. Boyden, Hanspeter Pfister, Donglai Wei
Publikováno v:
IEEE Journal of Biomedical and Health Informatics. :1-10
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5e407194cd8d3fc35b3e669a53cb3634
https://doi.org/10.1109/jbhi.2023.3281332
https://doi.org/10.1109/jbhi.2023.3281332
Autor:
Xiaomeng Han, Xiaotang Lu, Peter H. Li, Shuohong Wang, Richard Schalek, Yaron Meirovitch, Zudi Lin, Jason Adhinarta, Daniel Berger, Yuelong Wu, Tao Fang, Elif Sevde Meral, Shadnan Asraf, Hidde Ploegh, Hanspeter Pfister, Donglai Wei, Viren Jain, James S. Trimmer, Jeff W. Lichtman
Publikováno v:
bioRxiv
Mapping neuronal networks that underlie behavior has become a central focus in neuroscience. While serial section electron microscopy (ssEM) can reveal the fine structure of neuronal networks (connectomics), it does not provide the molecular informat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::81c102e280bab3d0c66ec50af1d5be4a
https://doi.org/10.1101/2023.05.20.540091
https://doi.org/10.1101/2023.05.20.540091
Autor:
Donglai Wei, Hanspeter Pfister, Ignacio Arganda-Carreras, Stephan Huschauer, Dorsa Ziaei, Yanling Liu, Martin Jones, Luke Nightingale, Jozefus De Folter, Ryan Conrad, Constantin Pape, Xuejin Chen, Jie Zhao, Zhili Li, Huai Chen, Hao Liu, Rui Xin, Zhiwei Xiong, Chang Chen, Mingxing Li, Yutian Fan, Wenjie Yin, Qijia Shen, Xueying Wang, Won-Dong Jang, Zudi Lin, Daniel Franco-Barranco
In this paper, we present the results of the MitoEM challenge on mitochondria 3D instance segmentation from electron microscopy images, organized in conjunction with the IEEE-ISBI 2021 conference. Our benchmark dataset consists of two large-scale 3D
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2162fa5d2fc2f95d12b43df6bf5a1c74
https://doi.org/10.36227/techrxiv.22116785
https://doi.org/10.36227/techrxiv.22116785
Publikováno v:
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6920e1caaa8c1760aad2a7e40e39473a
https://doi.org/10.1109/wacv56688.2023.00226
https://doi.org/10.1109/wacv56688.2023.00226
Publikováno v:
Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit
Evaluation practices for image super-resolution (SR) use a single-value metric, the PSNR or SSIM, to determine model performance. This provides little insight into the source of errors and model behavior. Therefore, it is beneficial to move beyond th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1626839c01487a334ef1d0b6fab05631
https://doi.org/10.1109/cvpr52688.2022.00216
https://doi.org/10.1109/cvpr52688.2022.00216
Autor:
Donglai Wei, Siddhant Kharbanda, Sarthak Arora, Roshan Roy, Nishant Jain, Akash Palrecha, Tanav Shah, Shray Mathur, Ritik Mathur, Abhijay Kemkar, Anirudh Chakravarthy, Zudi Lin, Won-Dong Jang, Yansong Tang, Song Bai, James Tompkin, Philip H.S. Torr, Hanspeter Pfister
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
Many video understanding tasks require analyzing multishot videos, but existing datasets for video object segmentation (VOS) only consider single-shot videos. To address this challenge, we collected a new dataset-YouMVaS-of 200 popular YouTube videos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b79df2fd0926845c23db343ec4539f7
https://doi.org/10.1109/cvpr52688.2022.02037
https://doi.org/10.1109/cvpr52688.2022.02037
Autor:
Yuanhao Cai, Jing Lin, Zudi Lin, Haoqian Wang, Yulun Zhang, Hanspeter Pfister, Radu Timofte, Luc Van Gool
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
Existing leading methods for spectral reconstruction (SR) focus on designing deeper or wider convolutional neural networks (CNNs) to learn the end-to-end mapping from the RGB image to its hyperspectral image (HSI). These CNN-based methods achieve imp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e087b6ae9c83bfc84943fe9688fc2f44
https://doi.org/10.1109/cvprw56347.2022.00090
https://doi.org/10.1109/cvprw56347.2022.00090
Autor:
Philipp Velicky, Eder Miguel, Julia M. Michalska, Donglai Wei, Zudi Lin, Jake F. Watson, Jakob Troidl, Johanna Beyer, Yoav Ben-Simon, Christoph Sommer, Wiebke Jahr, Alban Cenameri, Johannes Broichhagen, Seth G. N. Grant, Peter Jonas, Gaia Novarino, Hanspeter Pfister, Bernd Bickel, Johann G. Danzl
Publikováno v:
bioRxiv
biorXiv
biorXiv
Complex wiring between neurons underlies the information-processing network enabling all brain functions, including cognition and memory. For understanding how the network is structured, processes information, and changes over time, comprehensive vis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0663cb93d9f97a4b3000f82bdd16972c
https://doi.org/10.1101/2022.03.16.484431
https://doi.org/10.1101/2022.03.16.484431
Autor:
Boaz Arad, Radu Timofte, Rony Yahel, Nimrod Morag, Amir Bernat, Yuanhao Cai, Jing Lin, Zudi Lin, Haoqian Wang, Yulun Zhang, Hanspeter Pfister, Luc Van Gool, Shuai Liu, Yongqiang Li, Chaoyu Feng, Lei Lei, Jiaojiao Li, Songcheng Du, Chaoxiong Wu, Yihong Leng, Rui Song, Mingwei Zhang, Chongxing Song, Shuyi Zhao, Zhiqiang Lang, Wei Wei, Lei Zhang, Renwei Dian, Tianci Shan, Anjing Guo, Chengguo Feng, Jinyang Liu, Mirko Agarla, Simone Bianco, Marco Buzzelli, Luigi Celona, Raimondo Schettini, Jiang He, Yi Xiao, Jiajun Xiao, Qiangqiang Yuan, Jie Li, Liangpei Zhang, Taesung Kwon, Dohoon Ryu, Hyokyoung Bae, Hao-Hsiang Yang, Hua-En Chang, Zhi-Kai Huang, Wei-Ting Chen, Sy-Yen Kuo, Junyu Chen, Haiwei Li, Song Liu, Sabarinathan Sabarinathan, K Uma, B Sathya Bama, S. Mohamed Mansoor Roomi
This paper reviews the third biennial challenge on spectral reconstruction from RGB images, i.e., the recovery of whole-scene hyperspectral (HS) information from a 3-channel RGB image. This challenge presents the "ARAD_1K"data set: a new, larger-than
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b14c6f9646b01a471ce946e43634fa64
http://hdl.handle.net/11583/2971543
http://hdl.handle.net/11583/2971543