Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Amit Bermano"'
Autor:
Anna Giulia Pavon, Pier Giorgio Masci, Lorenzo Pucci, Antonio Landi, Amit Bermano, Amir Vaxman, Craig Gotsman, Tobias Rutz, Pierre Monney, Rita Godihno, David Saraiva Rodrigues, Olivier Muller, Marco Valgimigli, Juerg Schwitter
Publikováno v:
The International Journal of Cardiovascular Imaging. 38:1533-1543
Left atrium (LA) plays a key role in the overall cardiac performance. However, it remains unclear how LA adapts, in terms of function and volumes, to left ventricular dysfunction in the acute and post-acute phases of myocardial infarction. LA volumes
Autor:
Yotam Erel, Katherine Adams Shannon, Junyi Chu, Kim Scott, Melissa Kline Struhl, Peng Cao, Xincheng Tan, Peter Hart, Gal Raz, Sabrina Piccolo, Catherine Mei, Christine Potter, Sagi Jaffe-Dax, Casey Lew-Williams, Joshua Tenenbaum, Katherine Fairchild, Amit Bermano, Shari Liu
Publikováno v:
Advances in Methods and Practices in Psychological Science. 6:251524592211472
Technological advances in psychological research have enabled large-scale studies of human behavior and streamlined pipelines for automatic processing of data. However, studies of infants and children have not fully reaped these benefits because the
Autor:
Yotam Erel, Kat Adams Shannon, Junyi Chu, Kimberly Megan Scott, Melissa Kline Struhl, Peng Cao, Xincheng Tan, Peter K Hart, Gal Raz, Sabrina Piccolo, Catherine Mei, Christine Potter, Sagi Jaffe-Dax, Casey Lew-Williams, Joshua Tenenbaum, Katherine Fairchild, Amit Bermano, Shari Liu
Technological advances in psychological research have enabled large-scale studies of human behavior and streamlined pipelines for automatic processing of data. However, studies of infants and children have not fully reaped these benefits, because the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6aab81aa11563894a3f1e46385acaa1e
https://doi.org/10.31234/osf.io/up97k
https://doi.org/10.31234/osf.io/up97k
Publikováno v:
Computer Graphics Forum. 40:249-265
The task of unsupervised image-to-image translation has seen substantial advancements in recent years through the use of deep neural networks. Typically, the proposed solutions learn the characterizing distribution of two large, unpaired collections
Publikováno v:
ACM Transactions on Graphics. 39:1-14
Learning disentangled representations of data is a fundamental problem in artificial intelligence. Specifically, disentangled latent representations allow generative models to control and compose the disentangled factors in the synthesis process. Cur
Autor:
Ben Maman, Amit Bermano
Publikováno v:
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
The ability of Generative Adversarial Networks to encode rich semantics within their latent space has been widely adopted for facial image editing. However, replicating their success with videos has proven challenging. Sets of high-quality facial vid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8361b1ee768b23fdad79f3dfd8597170
Publikováno v:
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW).
Image augmentation techniques apply transformation functions such as rotation, shearing, or color distortion on an input image. These augmentations were proven useful in improving neural networks' generalization ability. In this paper, we present a n
Publikováno v:
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW).
Infants’ looking behaviors are often used for measuring attention, real-time processing, and learning – often using low-resolution videos. Despite the ubiquity of gaze-related methods in developmental science, current analysis techniques usually
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8045d2ca1bc1e9fa8b1710ac1a6981bf
https://doi.org/10.31234/osf.io/6ysu9
https://doi.org/10.31234/osf.io/6ysu9