Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Muhammad Atta Othman Ahmed"'
Publikováno v:
Brain Informatics, Vol 11, Iss 1, Pp 1-13 (2024)
Abstract In the field of audiology, achieving accurate discrimination of auditory impairments remains a formidable challenge. Conditions such as deafness and tinnitus exert a substantial impact on patients’ overall quality of life, emphasizing the
Externí odkaz:
https://doaj.org/article/4dc47647817c4c4388f2d1166e628bb2
Publikováno v:
BMC Medical Imaging, Vol 23, Iss 1, Pp 1-15 (2023)
Abstract Continuous release of image databases with fully or partially identical inner categories dramatically deteriorates the production of autonomous Computer-Aided Diagnostics (CAD) systems for true comprehensive medical diagnostics. The first ch
Externí odkaz:
https://doaj.org/article/5eac14c076b2411a942e8c341f1bd23c
Publikováno v:
Theoretical and Applied Informatics. 29:25-39
The concept of `diversity' has been one of the main open issues in the field of multiple classifier systems. In this paper we address a facet of diversity related to its effectiveness for ensemble construction, namely, explicitly using diversity meas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::33be5792651ea791d011d725fc468af1
https://doi.org/10.20904/291-2025
https://doi.org/10.20904/291-2025
Autor:
Fathi E. Abd El-Samie, Hani Abd El-Rahaman, Basma Abd El-Rahiem, Mohamed Amin, Omar Reyad, Muhammad Atta Othman Ahmed
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030141172
AMLTA
AMLTA
Such a hot open issue in the area of computer vision is the classification of visual images especially in Internet of Things (IoT) and remote mid-band and high-band based connections. In this paper, we propose a robust and efficient taxonomy framewor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::08ae27323ed6d63391dfb5864a27e5b3
https://doi.org/10.1007/978-3-030-14118-9_3
https://doi.org/10.1007/978-3-030-14118-9_3
Autor:
MUHAMMAD ATTA OTHMAN AHMED
Publikováno v:
MUHAMMAD ATTA OTHMAN AHMED
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c105a98a9a894a3336d831b73d3f401c
Publikováno v:
The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018) ISBN: 9783319746890
AMLTA
AMLTA
One of the goals of person re-identification systems is to support video-surveillance operators and forensic investigators to find an individual of interest in videos acquired by a network of non-overlapping cameras. This is attained by sorting image
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::35fe5b647542bc270c9103334c0f3296
https://doi.org/10.1007/978-3-319-74690-6_15
https://doi.org/10.1007/978-3-319-74690-6_15
Publikováno v:
The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018) ISBN: 9783319746890
AMLTA
AMLTA
Biometric systems are widely used in various applications of today’s authentication technology. The unimodal systems suffer from various stumbling blocks such as noisy inputs, non-universality, intra-class variability and imposter spoofing which af
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ffb99bf7157b086956aeeaab560147be
https://doi.org/10.1007/978-3-319-74690-6_61
https://doi.org/10.1007/978-3-319-74690-6_61
Autor:
Muhammad Atta Othman Ahmed
Publikováno v:
The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018) ISBN: 9783319746890
AMLTA
AMLTA
Randomization ensemble creation technique well-known as Bagging is widely used to construct trained ensembles of base classifiers. The computational power and demand of Neural Networks (NNs) approved in both researches or in applications. The weight
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2ba0cf5028b3d2e44d2cca5789dffee9
https://doi.org/10.1007/978-3-319-74690-6_24
https://doi.org/10.1007/978-3-319-74690-6_24
Publikováno v:
Multiple Classifier Systems ISBN: 9783319202471
MCS
MCS
We address one of the main open issues about the use of diversity in multiple classifier systems: the effectiveness of the explicit use of diversity measures for creation of classifier ensembles. So far, diversity measures have been mostly used for e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6dd74f1f6a6f841fb2ae9a2045b7a021
https://hdl.handle.net/11567/1086099
https://hdl.handle.net/11567/1086099