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Wandile Nhlapho, Marcellin Atemkeng, Yusuf Brima and Jean-Claude Ndogmo
The advent of deep learning (DL) has revolutionized medical imaging, offering unprecedented avenues for accurate disease classification and diagnosis. DL models have shown remarkable promise for classifying brain tumors from Magnetic Resonance Imaging (M...
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Fabi Prezja, Leevi Annala, Sampsa Kiiskinen and Timo Ojala
Diagnosing knee joint osteoarthritis (KOA), a major cause of disability worldwide, is challenging due to subtle radiographic indicators and the varied progression of the disease. Using deep learning for KOA diagnosis requires broad, comprehensive dataset...
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Sarfaraz Natha, Umme Laila, Ibrahim Ahmed Gashim, Khalid Mahboob, Muhammad Noman Saeed and Khaled Mohammed Noaman
Brain tumors (BT) represent a severe and potentially life-threatening cancer. Failing to promptly diagnose these tumors can significantly shorten a person?s life. Therefore, early and accurate detection of brain tumors is essential, allowing for appropri...
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Jiwun Yoon, Sang-Yong Lee and Ji-Yong Lee
Humans share a similar body structure, but each individual possesses unique characteristics, which we define as one?s body type. Various classification methods have been devised to understand and assess these body types. Recent research has applied artif...
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Seokjoon Kwon, Jae-Hyeon Park, Hee-Deok Jang, Hyunwoo Nam and Dong Eui Chang
Deep learning algorithms are widely used for pattern recognition in electronic noses, which are sensor arrays for gas mixtures. One of the challenges of using electronic noses is sensor drift, which can degrade the accuracy of the system over time, even ...
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