← Назад к работе
Работы, на которые ссылается эта работа
Работ: 32
Работа: Real-time deep learning semantic segmentation during intra-operative surgery for 3D augmented reality assistance
Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren +1
Статья2016Цитирований: 61ABIU-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger, Philipp Fischer, Thomas Brox
Глава2015Цитирований: 32ABIA guide to deep learning in healthcare
Andre Esteva, Alexandre Robicquet, Bharath Ramsundar +7
Обзорная статья2018Цитирований: 4ABIMachine learning applications in cancer prognosis and prediction
Κωνσταντίνα Κούρου, Themis P. Exarchos, Konstantinos Exarchos +2
Обзорная статья2014Цитирований: 3ABIPyramid Scene Parsing Network
Hengshuang Zhao, Jianping Shi, Xiaojuan Qi +2
Статья2017Цитирований: 3ABITopological structural analysis of digitized binary images by border following
Статья1985Цитирований: 2ABIEndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos
Andru Putra Twinanda, Sherif Shehata, Didier Mutter +3
Статья2016Цитирований: 2ABIParsing human skeletons in an operating room
Vasileios Belagiannis, Xinchao Wang, Horesh Beny Ben Shitrit +9
Статья2016Цитирований: 2ABIThe status of augmented reality in laparoscopic surgery as of 2016
Sylvain Bernhardt, Stéphane Nicolau, Luc Soler +1
Обзорная статья2017Цитирований: 2ABIMobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew Howard, Menglong Zhu, Bo Chen +5
Препринт2017Цитирований: 2ABISV-RCNet: Workflow Recognition From Surgical Videos Using Recurrent Convolutional Network
Yueming Jin, Qi Dou, Hao Chen +4
Статья2017Цитирований: 2ABISpiking Neural Networks for early prediction in human–robot collaboration
Статья2019Цитирований: 2ABI3D augmentation of the surgical video stream: Toward a modular approach
Marco Gribaudo, Pietro Piazzolla, Francesco Porpiglia +2
Статья2020Цитирований: 2ABI