Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Muneer A. Dedmari"'
Publikováno v:
Frontiers in Plant Science, Vol 13 (2022)
Saffron authenticity is important for the saffron industry, consumers, food industry, and regulatory agencies. Herein we describe a combo of two novel methods to distinguish genuine saffron from fake in a user-friendly manner and without sophisticate
Externí odkaz:
https://doaj.org/article/ad3488ed8b75448385761765f7dcd89e
Autor:
Guilherme Aresta, Chandan Panda, Gwenole Quellec, Senthil Ramamurthy, Xiaowei Hu, Adrian Galdran, Navdeep Dahiya, Fenqiang Zhao, Pheng-Ann Heng, Evangello Flouty, William G. Macready, Danail Stoyanov, Sailesh Conjeti, Anirban Mukhopadhyay, Sabrina Dill, Stefan Zachow, Jogundas Armaitis, Mathieu Lamard, Pedro Alves Costa, Shunren Xia, Jonas Prellberg, Manish Sahu, Satoshi Kondo, Pierre-Henri Conze, Muneer Ahmad Dedmari, Chenhui Qiu, Arash Vahdat, Gabija Maršalkaitė, Zhengbing Bian, Jonas Bialopetravičius, Duc My Vo, Soumali Roychowdhury, Béatrice Cochener, Odysseas Zisimopoulos, Teresa Araújo, Sang-Woong Lee, Hassan Al Hajj, Aurélio Campilho
Publikováno v:
Medical image analysis 52, 24-41 (2019). doi:10.1016/j.media.2018.11.008
Medical Image Analysis
Medical Image Analysis, Elsevier, 2019, 52, pp.24-41. ⟨10.1016/j.media.2018.11.008⟩
Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
Medical Image Analysis
Medical Image Analysis, Elsevier, 2019, 52, pp.24-41. ⟨10.1016/j.media.2018.11.008⟩
Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
International audience; Surgical tool detection is attracting increasing attention from the medical image analysis community. The goal generally is not to precisely locate tools in images, but rather to indicate which tools are being used by the surg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1ad218fc3c2f9be6d2628dad3a7b9c25
https://pub.dzne.de/record/140461
https://pub.dzne.de/record/140461
Autor:
Muneer Ahmad Dedmari, Santiago Estrada, Phillip Ehses, Sailesh Conjeti, Tony Stöcker, Martin Reuter
Publikováno v:
MLMIR 2018, Granada, Spain, 2018-09-16-2018-09-16
Machine Learning for Medical Image Reconstruction ISBN: 9783030001285
MLMIR@MICCAI
Machine Learning for Medical Image Reconstruction ISBN: 9783030001285
MLMIR@MICCAI
Undersampling the k-space data is widely adopted for acceleration of Magnetic Resonance Imaging (MRI). Current deep learning based approaches for supervised learning of MRI image reconstruction employ real-valued operations and representations by tre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6b73bb4af67d62000457b6b7ed4d8fef
http://arxiv.org/abs/1807.03343
http://arxiv.org/abs/1807.03343