Zobrazeno 1 - 2
of 2
pro vyhledávání: '"Abdar, M. (Moloud)"'
Autor:
Abdar, M. (Moloud), Pourpanah, F. (Farhad), Hussain, S. (Sadiq), Rezazadegan, D. (Dana), Liu, L. (Li), Ghavamzadeh, M. (Mohammad), Fieguth, P. (Paul), Cao, X. (Xiaochun), Khosravi, A. (Abbas), Acharya, U. R. (U. Rajendra), Makarenkov, V. (Vladimir), Nahavandi, S. (Saeid)
Uncertainty quantification (UQ) methods play a pivotal role in reducing the impact of uncertainties during both optimization and decision making processes. They have been applied to solve a variety of real-world problems in science and engineering. B
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2423::9617ee124ea733924dc3b09fd6b341d8
http://urn.fi/urn:nbn:fi-fe2021090645179
http://urn.fi/urn:nbn:fi-fe2021090645179
Autor:
Abdar, M. (Moloud), Samami, M. (Maryam), Mahmoodabad, S. D. (Sajjad Dehghani), Doan, T. (Thang), Mazoure, B. (Bogdan), Hashemifesharaki, R. (Reza), Liu, L. (Li), Khosravi, A. (Abbas), Acharya, U. R. (U. Rajendra), Makarenkov, V. (Vladimir), Nahavandi, S. (Saeid)
Accurate automated medical image recognition, including classification and segmentation, is one of the most challenging tasks in medical image analysis. Recently, deep learning methods have achieved remarkable success in medical image classification
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2423::0025b6f6035f07108d3ad77b409f55ed
http://urn.fi/urn:nbn:fi-fe2022030121347
http://urn.fi/urn:nbn:fi-fe2022030121347