Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Tahsin M. Kurc"'
Autor:
Sarthak Pati, Siddhesh P. Thakur, İbrahim Ethem Hamamcı, Ujjwal Baid, Bhakti Baheti, Megh Bhalerao, Orhun Güley, Sofia Mouchtaris, David Lang, Spyridon Thermos, Karol Gotkowski, Camila González, Caleb Grenko, Alexander Getka, Brandon Edwards, Micah Sheller, Junwen Wu, Deepthi Karkada, Ravi Panchumarthy, Vinayak Ahluwalia, Chunrui Zou, Vishnu Bashyam, Yuemeng Li, Babak Haghighi, Rhea Chitalia, Shahira Abousamra, Tahsin M. Kurc, Aimilia Gastounioti, Sezgin Er, Mark Bergman, Joel H. Saltz, Yong Fan, Prashant Shah, Anirban Mukhopadhyay, Sotirios A. Tsaftaris, Bjoern Menze, Christos Davatzikos, Despina Kontos, Alexandros Karargyris, Renato Umeton, Peter Mattson, Spyridon Bakas
Publikováno v:
Communications Engineering. 2
Deep Learning (DL) has the potential to optimize machine learning in both the scientific and clinical communities. However, greater expertise is required to develop DL algorithms, and the variability of implementations hinders their reproducibility,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::582c3268dccbedca61bf53a84270b00a
https://doi.org/10.1038/s44172-023-00066-3
https://doi.org/10.1038/s44172-023-00066-3
Autor:
Willian Barreiros, Alba C.M.A. Melo, Jun Kong, Renato Ferreira, Tahsin M. Kurc, Joel H. Saltz, George Teodoro
Publikováno v:
Journal of Parallel and Distributed Computing. 164:40-54
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2fe1c32790e2966f928a004b5d083841
https://doi.org/10.1016/j.jpdc.2022.02.004
https://doi.org/10.1016/j.jpdc.2022.02.004
Autor:
Jakub R. Kaczmarzyk, Rajarsi Gupta, Tahsin M. Kurc, Shahira Abousamra, Joel H. Saltz, Peter K. Koo
Publikováno v:
Computer Methods and Programs in Biomedicine. :107631
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1871c85ceeea3765321f0b48b9ca0d7a
https://doi.org/10.1016/j.cmpb.2023.107631
https://doi.org/10.1016/j.cmpb.2023.107631
Publikováno v:
Journal of Pathology Informatics, Vol 8, Iss 1, Pp 38-38 (2017)
Context: Image segmentation pipelines often are sensitive to algorithm input parameters. Algorithm parameters optimized for a set of images do not necessarily produce good-quality-segmentation results for other images. Even within an image, some regi
Externí odkaz:
https://doaj.org/article/6034f19f472543998fd17948a2a2b1af
Publikováno v:
Proceedings of machine learning research. 54
Within Neural Networks (NN), the parameters of Adaptive Activation Functions (AAF) control the shapes of activation functions. These parameters are trained along with other parameters in the NN. AAFs have improved performance of Convolutional Neural
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::3fc8581ed98b3ca5d243be1d282ad58b
https://pubmed.ncbi.nlm.nih.gov/31106299
https://pubmed.ncbi.nlm.nih.gov/31106299
Autor:
Tony C, Pan, Metin N, Gurcan, Stephen A, Langella, Scott W, Oster, Shannon L, Hastings, Ashish, Sharma, Benjamin G, Rutt, David W, Ervin, Tahsin M, Kurc, Khan M, Siddiqui, Joel H, Saltz, Eliot L, Siegel
Publikováno v:
Radiographics : a review publication of the Radiological Society of North America, Inc. 27(3)
Grid computing-the use of a distributed network of electronic resources to cooperatively perform subsets of computationally intensive tasks-may help improve the speed and accuracy of radiologic image interpretation by enabling collaborative computer-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::6c45900f14d8dcd32833dd95520ddb4e
https://pubmed.ncbi.nlm.nih.gov/17495299
https://pubmed.ncbi.nlm.nih.gov/17495299