Analysis of traditional and deep learning-based approaches to extract informative signs of skin cancer from dermatoscopic images

Bobokhonov, Akhmadkhon

Al-Farg'oniy avlodlari · 2026-yil

Annotatsiya

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.

Maqola ma’lumotlari
MualliflarBobokhonov, Akhmadkhon
JurnalAl-Farg'oniy avlodlari
Nashr sanasi2026-03-06
Son1
Betlar110-118
TilRus

Kalit so‘zlar

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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