Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Shimaa El-bana"'
Publikováno v:
IEEE Access, Vol 11, Pp 51199-51213 (2023)
Wavelet pooling (WP) in neural network architectures has recently demonstrated more discriminative power than traditional pooling methods. This is mainly because the latter suffer from spatial information loss while wavelet pooling harnesses the powe
Externí odkaz:
https://doaj.org/article/c3a50387d9c843e4a560b7601c279d30
Publikováno v:
IEEE Access, Vol 10, Pp 59592-59602 (2022)
We are concerned with the development of effective training strategies for light-weight deep networks, which facilitates harnessing the power of deep learning on hand-held devices. A vast literature has focused on enhancing the performance of deep co
Externí odkaz:
https://doaj.org/article/74dd56e9d57740fc89266af619094158
Publikováno v:
PeerJ Computer Science, Vol 6, p e303 (2020)
We are concerned with the challenge of coronavirus disease (COVID-19) detection in chest X-ray and Computed Tomography (CT) scans, and the classification and segmentation of related infection manifestations. Even though it is arguably not an establis
Externí odkaz:
https://doaj.org/article/5e0cfcc2471d4d03b001151db8078e0a
Publikováno v:
Diagnostics, Vol 10, Iss 3, p 131 (2020)
This research is concerned with malignant pulmonary nodule detection (PND) in low-dose CT scans. Due to its crucial role in the early diagnosis of lung cancer, PND has considerable potential in improving the survival rate of patients. We propose a tw
Externí odkaz:
https://doaj.org/article/57700eceeb044f1aa2b94782b7444ff3
Publikováno v:
2021 38th National Radio Science Conference (NRSC).
MobileNet is a light-weight neural network model that has facilitated harnessing the power of deep learning on mobile devices. The advances in pervasive computing and the ever-increasing interest in deep learning has resulted in a growing research at
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b61383bf06fef69102660d999afc091d
https://doi.org/10.1109/nrsc52299.2021.9509825
https://doi.org/10.1109/nrsc52299.2021.9509825
Publikováno v:
2021 International Telecommunications Conference (ITC-Egypt).
Aerial scene classification using multi-label remote sensing (MLRS) is a remote sensing challenge task. Conventional techniques in this research area have mainly focused either on the simplified single-label case or on pixel-based approaches, which c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::698a4f3544611af91a8722cdd62f0187
https://doi.org/10.1109/itc-egypt52936.2021.9513885
https://doi.org/10.1109/itc-egypt52936.2021.9513885
Publikováno v:
PeerJ Computer Science, Vol 6, p e303 (2020)
PeerJ Computer Science
PeerJ Computer Science
We are concerned with the challenge of coronavirus disease (COVID-19) detection in chestX-ray and Computed Tomography (CT) scans, and the classification and segmentation of relatedinfection manifestations. Even though it is arguably not an establishe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::13faa0bb41f7a49dff138f7e2e98a186
https://peerj.com/articles/cs-303.pdf
https://peerj.com/articles/cs-303.pdf
Publikováno v:
Diagnostics, Vol 10, Iss 3, p 131 (2020)
Diagnostics
Volume 10
Issue 3
Diagnostics
Volume 10
Issue 3
This research is concerned with malignant pulmonary nodule detection (PND) in low-dose CT scans. Due to its crucial role in the early diagnosis of lung cancer, PND has considerable potential in improving the survival rate of patients. We propose a tw
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd486a4dc23d5f84ea6b313b012317d8
https://doi.org/10.3390/diagnostics10030131
https://doi.org/10.3390/diagnostics10030131