Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Dihong Gong"'
Autor:
Dihong Gong, Juanhong Lei, Xudong He, Junjie Hao, Fan Zhang, Xinya Huang, Wen Gu, Xinxin Yang, Jie Yu
Publikováno v:
Lipids in Health and Disease, Vol 23, Iss 1, Pp 1-27 (2024)
Abstract As one of the main pathogenic factors of cardiovascular and cerebrovascular diseases, the incidence of metabolic diseases such as adiposity and metabolic dysfunction-associated steatotic liver disease (MASLD) is increasing annually. It is ur
Externí odkaz:
https://doaj.org/article/143c4efba41047188e38323ed78c474c
Autor:
Sergio Marconi, Sarah J. Graves, Dihong Gong, Morteza Shahriari Nia, Marion Le Bras, Bonnie J. Dorr, Peter Fontana, Justin Gearhart, Craig Greenberg, Dave J. Harris, Sugumar Arvind Kumar, Agarwal Nishant, Joshi Prarabdh, Sundeep U. Rege, Stephanie Ann Bohlman, Ethan P. White, Daisy Zhe Wang
Publikováno v:
PeerJ, Vol 6, p e5843 (2019)
Ecology has reached the point where data science competitions, in which multiple groups solve the same problem using the same data by different methods, will be productive for advancing quantitative methods for tasks such as species identification fr
Externí odkaz:
https://doaj.org/article/d5db38cd8de94758a70ea670b9865530
Publikováno v:
Cancer Informatics, Vol 2014, Iss Suppl. 3, Pp 15-31 (2014)
Externí odkaz:
https://doaj.org/article/d9de2ccbaa8548cfa3631649272497bc
Publikováno v:
IEEE Transactions on Image Processing. 30:1219-1231
General image super-resolution techniques have difficulties in recovering detailed face structures when applying to low resolution face images. Recent deep learning based methods tailored for face images have achieved improved performance by jointly
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b0b9476199104e4be917df844f426927
https://doi.org/10.1109/tip.2020.3043093
https://doi.org/10.1109/tip.2020.3043093
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031200649
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::44da0a6121ae908dace5105b3a872bed
https://doi.org/10.1007/978-3-031-20065-6_7
https://doi.org/10.1007/978-3-031-20065-6_7
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031200649
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::684a9276cd88899d8e0d9751313e5b27
https://doi.org/10.1007/978-3-031-20065-6_10
https://doi.org/10.1007/978-3-031-20065-6_10
Publikováno v:
IEEE transactions on pattern analysis and machine intelligence. 44(10)
With the recent advancement of deep convolutional neural networks, significant progress has been made in general face recognition. However, the state-of-the-art general face recognition models do not generalize well to occluded face images, which are
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::adf4ad335bc92e6885d522e11567ec3e
https://pubmed.ncbi.nlm.nih.gov/34310287
https://pubmed.ncbi.nlm.nih.gov/34310287
Publikováno v:
ICCV
Deep Convolutional Neural Networks (CNNs) have been pushing the frontier of face recognition over past years. However, existing CNN models are far less accurate when handling partially occluded faces. These general face models generalize poorly for o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::748dc8d6c229cffadbb41f0a15eb45ff
https://doi.org/10.1109/iccv.2019.00086
https://doi.org/10.1109/iccv.2019.00086
Publikováno v:
CVPR
There has been an increasing research interest in age-invariant face recognition. However, matching faces with big age gaps remains a challenging problem, primarily due to the significant discrepancy of face appearances caused by aging. To reduce suc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::12a243409c3b930e8adba9e6deba7721
https://doi.org/10.1109/cvpr.2019.00364
https://doi.org/10.1109/cvpr.2019.00364
Publikováno v:
CVPR
Face anti-spoofing is an important task in full-stack face applications including face detection, verification, and recognition. Previous approaches build models on datasets which do not simulate the real-world data well (e.g., small scale, insignifi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a5261bf443bd3168223d8ddd67b1b738
https://doi.org/10.1109/cvpr.2019.00362
https://doi.org/10.1109/cvpr.2019.00362