Zobrazeno 1 - 10
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pro vyhledávání: '"Abdelsamea, Mohammed M"'
Autor:
Senousy, Zakaria, Abdelsamea, Mohammed M., Gaber, Mohamed Medhat, Abdar, Moloud, Acharya, U Rajendra, Khosravi, Abbas, Nahavandi, Saeid
Publikováno v:
IEEE Transactions on Biomedical Engineering 2021
Breast histology image classification is a crucial step in the early diagnosis of breast cancer. In breast pathological diagnosis, Convolutional Neural Networks (CNNs) have demonstrated great success using digitized histology slides. However, tissue
Externí odkaz:
http://arxiv.org/abs/2108.10709
Due to the high availability of large-scale annotated image datasets, knowledge transfer from pre-trained models showed outstanding performance in medical image classification. However, building a robust image classification model for datasets with d
Externí odkaz:
http://arxiv.org/abs/2007.11450
Chest X-ray is the first imaging technique that plays an important role in the diagnosis of COVID-19 disease. Due to the high availability of large-scale annotated image datasets, great success has been achieved using convolutional neural networks (C
Externí odkaz:
http://arxiv.org/abs/2003.13815
Publikováno v:
In Expert Systems With Applications 15 April 2023 216
Akademický článek
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Autor:
Ibrahim, Asmaa, Gamble, Paul, Jaroensri, Ronnachai, Abdelsamea, Mohammed M., Mermel, Craig H., Chen, Po-Hsuan Cameron, Rakha, Emad A.
Publikováno v:
In The Breast February 2020 49:267-273
Autor:
Abdelsamea, Mohammed M.
In this paper, an automatic seeded region growing algorithm is proposed for cellular image segmentation. First, the regions of interest (ROIs) extracted from the preprocessed image. Second, the initial seeds are automatically selected based on ROIs e
Externí odkaz:
http://arxiv.org/abs/1412.3958
Autor:
Abdelsamea, Mohammed M.
Publikováno v:
2011 International Conference on Signal, Image Processing and Applications With workshop of ICEEA 2011, IPCSIT vol.21 (2011), IACSIT Press, Singapore
SOM is a type of unsupervised learning where the goal is to discover some underlying structure of the data. In this paper, a new extraction method based on the main idea of Concurrent Self-Organizing Maps (CSOM), representing a winner-takes-all colle
Externí odkaz:
http://arxiv.org/abs/1408.4504
Texture is one of the most important properties of visual surface that helps in discriminating one object from another or an object from background. The self-organizing map (SOM) is an excellent tool in exploratory phase of data mining. It projects i
Externí odkaz:
http://arxiv.org/abs/1408.4143
Autor:
Abdelsamea, Mohammed M.
A good segmentation result depends on a set of "correct" choice for the seeds. When the input images are noisy, the seeds may fall on atypical pixels that are not representative of the region statistics. This can lead to erroneous segmentation result
Externí odkaz:
http://arxiv.org/abs/1407.3664