Zobrazeno 1 - 10
of 70
pro vyhledávání: '"Lorenzo Torresani"'
Publikováno v:
Journal of Pathology Informatics, Vol 14, Iss , Pp 100320- (2023)
Deep learning has been effective for histology image analysis in digital pathology. However, many current deep learning approaches require large, strongly- or weakly labeled images and regions of interest, which can be time-consuming and resource-int
Externí odkaz:
https://doaj.org/article/7fa19128237e46c1b69f282c1adc8b10
Autor:
Bruno Korbar, Andrea M Olofson, Allen P Miraflor, Catherine M Nicka, Matthew A Suriawinata, Lorenzo Torresani, Arief A Suriawinata, Saeed Hassanpour
Publikováno v:
Journal of Pathology Informatics, Vol 8, Iss 1, Pp 30-30 (2017)
Context: Histopathological characterization of colorectal polyps is critical for determining the risk of colorectal cancer and future rates of surveillance for patients. However, this characterization is a challenging task and suffers from significan
Externí odkaz:
https://doaj.org/article/fd5c4ad7a1344226b047c2a7a7bd5216
Publikováno v:
Artificial Intelligence in Medicine ISBN: 9783031093418
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::557fed4c8bdb5f9df074791c6ade63c5
https://doi.org/10.1007/978-3-031-09342-5_26
https://doi.org/10.1007/978-3-031-09342-5_26
Publikováno v:
ICASSP
Although speaker verification has conventionally been an audio-only task, some practical applications provide both audio and visual streams of input. In these cases, the visual stream provides complementary information and can often be leveraged in c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a958d32ee7cd2d983ddb644da06c4c36
https://doi.org/10.1109/icassp39728.2021.9414260
https://doi.org/10.1109/icassp39728.2021.9414260
Publikováno v:
CVPR
The standard way of training video models entails sampling at each iteration a single clip from a video and optimizing the clip prediction with respect to the video-level label. We argue that a single clip may not have enough temporal coverage to exh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e70c8ffc300e78c1515ed09e1c4b120a
https://doi.org/10.1109/cvpr46437.2021.00748
https://doi.org/10.1109/cvpr46437.2021.00748
Publikováno v:
CVPR
We present \textsc{Vx2Text}, a framework for text generation from multimodal inputs consisting of video plus text, speech, or audio. In order to leverage transformer networks, which have been shown to be effective at modeling language, each modality
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c975b8c7ca9d59ed252c034365fcca7
http://arxiv.org/abs/2101.12059
http://arxiv.org/abs/2101.12059
Autor:
Jerry Wei, Michael Baker, Lorenzo Torresani, Charles Brown, Bing Ren, Mikhail Lisovsky, Jason Wei, Louis J. Vaickus, Naofumi Tomita, Xiaoying Liu, Saeed Hassanpour, Arief A. Suriawinata
Publikováno v:
Artificial Intelligence in Medicine ISBN: 9783030772109
AIME
AIME
With the rise of deep learning, there has been increased interest in using neural networks for histopathology image analysis, a field that investigates the properties of biopsy or resected specimens traditionally manually examined under a microscope
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9ffd567c6be140c70c6391090e59c4c4
https://doi.org/10.1007/978-3-030-77211-6_2
https://doi.org/10.1007/978-3-030-77211-6_2
Autor:
Laura Sevilla-Lara, Vedanuj Goswami, Lorenzo Torresani, Zhicheng Yan, Shengxin Zha, Matt Feiszli
Publikováno v:
WACV
Understanding temporal information and how the visual world changes over time, is a fundamental ability of intelligent systems. In video understanding, temporal information is at the core of many current challenges, including compression, efficient i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::402f927d729c2c67cd994d1abaaeb0c8
https://doi.org/10.1109/wacv48630.2021.00058
https://doi.org/10.1109/wacv48630.2021.00058
Autor:
Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang, Miao Liu, Xingyu Liu, Miguel Martin, Tushar Nagarajan, Ilija Radosavovic, Santhosh Kumar Ramakrishnan, Fiona Ryan, Jayant Sharma, Michael Wray, Mengmeng Xu, Eric Zhongcong Xu, Chen Zhao, Siddhant Bansal, Dhruv Batra, Vincent Cartillier, Sean Crane, Tien Do, Morrie Doulaty, Akshay Erapalli, Christoph Feichtenhofer, Adriano Fragomeni, Qichen Fu, Abrham Gebreselasie, Cristina Gonzalez, James Hillis, Xuhua Huang, Yifei Huang, Wenqi Jia, Weslie Khoo, Jachym Kolar, Satwik Kottur, Anurag Kumar, Federico Landini, Chao Li, Yanghao Li, Zhenqiang Li, Karttikeya Mangalam, Raghava Modhugu, Jonathan Munro, Tullie Murrell, Takumi Nishiyasu, Will Price, Paola Ruiz Puentes, Merey Ramazanova, Leda Sari, Kiran Somasundaram, Audrey Southerland, Yusuke Sugano, Ruijie Tao, Minh Vo, Yuchen Wang, Xindi Wu, Takuma Yagi, Ziwei Zhao, Yunyi Zhu, Pablo Arbelaez, David Crandall, Dima Damen, Giovanni Maria Farinella, Christian Fuegen, Bernard Ghanem, Vamsi Krishna Ithapu, C. V. Jawahar, Hanbyul Joo, Kris Kitani, Haizhou Li, Richard Newcombe, Aude Oliva, Hyun Soo Park, James M. Rehg, Yoichi Sato, Jianbo Shi, Mike Zheng Shou, Antonio Torralba, Lorenzo Torresani, Mingfei Yan, Jitendra Malik
We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It offers 3,670 hours of daily-life activity video spanning hundreds of scenarios (household, outdoor, workplace, leisure, etc.) captured by 931 unique camera wearers f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1501461e84d5acdefffd137ee9ba374d
Autor:
Jason Wei, Louis J. Vaickus, Naofumi Tomita, Lorenzo Torresani, Jerry Wei, Bing Ren, Michael Baker, Arief A. Suriawinata, Mustafa Nasir-Moin, Charles Brown, Saeed Hassanpour, Xiaoying Liu, Mikhail Lisovsky
Publikováno v:
WACV
Applying curriculum learning requires both a range of difficulty in data and a method for determining the difficulty of examples. In many tasks, however, satisfying these requirements can be a formidable challenge. In this paper, we contend that hist
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::deb73523dd82bb146d90e51c51214470
http://arxiv.org/abs/2009.13698
http://arxiv.org/abs/2009.13698