In computer-aided diagnosis (CAD) systems, the extraction of disease-specific informative features (IBAO) plays an important role in the detection of skin cancer. The main goal of IBAO is to transform dermatoscopic images into a compact set of digital descriptors that store the most important pathological information of skin diseases. The features extracted from the images mainly describe important information such as color distribution, texture unevenness, shape asymmetry, and boundary deformation. In this study, traditional and DL-based approaches to IBAO of skin diseases from dermatoscopic images were analyzed.
| Mualliflar | Bobokhonov, Akhmadkhon |
|---|---|
| Jurnal | Al-Farg'oniy avlodlari |
| Nashr sanasi | 2026-03-06 |
| Son | 1 |
| Betlar | 110-118 |
| Til | Rus |
Informativ belgilarni ajratib olish, CAD, Teri saratoni, Chuqur o‘qitish (DL), Konvolyutsion neyron tarmoq (CNN)., Feature extraction, CAD, Skin cancer, Deep learning, Convolutional neural network
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