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pro vyhledávání: '"Quader, Niamul"'
Recent self-supervised video representation learning methods have found significant success by exploring essential properties of videos, e.g. speed, temporal order, etc. This work exploits an essential yet under-explored property of videos, the video
Externí odkaz:
http://arxiv.org/abs/2112.05883
Transferring knowledge learned from the labeled source domain to the raw target domain for unsupervised domain adaptation (UDA) is essential to the scalable deployment of autonomous driving systems. State-of-the-art methods in UDA often employ a key
Externí odkaz:
http://arxiv.org/abs/2111.15242
Action localization networks are often structured as a feature encoder sub-network and a localization sub-network, where the feature encoder learns to transform an input video to features that are useful for the localization sub-network to generate r
Externí odkaz:
http://arxiv.org/abs/2109.02613
Publikováno v:
In Ultrasound in Medicine & Biology January 2021 47(1):139-153
Publikováno v:
In Ultrasound in Medicine & Biology April 2020 46(4):921-935
Autor:
Quader, Niamul, Hodgson, Antony J., Mulpuri, Kishore, Schaeffer, Emily, Abugharbieh, Rafeef ∗
Publikováno v:
In Ultrasound in Medicine & Biology June 2017 43(6):1252-1262
Automatic characterization of developmental dysplasia of the hip in infants using ultrasound imaging
Autor:
Quader, Niamul
Developmental dysplasia of the hip (DDH) is the most common pediatric hip condition, representing a spectrum of hip abnormalities ranging from mild dysplasia to irreducible hip dislocation. Thirty-three years ago, the introduction of the Graf method
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5e0f5d15ddddb8998574ddc1947c8c43
Akademický článek
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Publikováno v:
Medical Image Computing & Computer-Assisted Intervention -- MICCAI 2016: Part I; 2016, p602-609, 8p
Publikováno v:
2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI); 2015, p13-16, 4p