Temat: skin segmentation - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Face detection in color images using skin segmentation
Autorzy:: Hajiarbabi, M.
Agah, A.
Powiązania:: https://bibliotekanauki.pl/articles/384677.pdf
Data publikacji:: 2014
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: skin detection
neural networks
face detection
skin segmentation
image processing
Opis:: Face detection which is a challenging problem in computer vision, can be used as a major step in face recognition. The challenges of face detection in color images include illumination differences, various cameras characteristics, different ethnicities, and other distinctions. In order to detect faces in color images, skin detection can be applied to the image. Numerous methods have been utilized for human skin color detection, including Gaussian model, rule-based methods, and artificial neural networks. In this paper, we present a novel neural network-based technique for skin detection, introducing a skin segmentation process for finding the faces in color images.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2014, 8, 3; 41-51
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Classification and detection of skin disease based on machine learning and image processing evolutionary models
Autorzy:: Bordoloi, Dibyahash
Singh, Vijay
Kaliyaperumal, Karthikeyan
Ritonga, Mahyudin
Jawarneh, Malik
Kassanuk, Thanwamas
Quiñonez-Choquecota, Jose
Powiązania:: https://bibliotekanauki.pl/articles/38700501.pdf
Data publikacji:: 2023
Wydawca:: Instytut Podstawowych Problemów Techniki PAN
Tematy:: skin disorder
machine learning
classification
image enhancement
image segmentation
disease detection
schorzenie skóry
nauczanie maszynowe
klasyfikacja
ulepszenie obrazu
segmentacja obrazów
wykrywanie choroby
Opis:: Skin disorders, a prevalent cause of illnesses, may be identified by studying their physical structure and history of the condition. Currently, skin diseases are diagnosed using invasive procedures such as clinical examination and histology. The examinations are quite effective and beneficial. This paper describes an evolutionary model for skin disease classification and detection based on machine learning and image processing. This model integrates image preprocessing, image augmentation, segmentation, and machine learning algorithms. The experimental investigation makes use of a dermatology data set. The model employs the machine learning methods: the support vector machine (SVM), the k-nearest neighbors (KNN), and random forest algorithms for image categorization and detection. This suggested methodology is beneficial for the accurate identification of skin disease using image analysis. The SVM algorithm achieved an accuracy of 98.8%. The KNN algorithm achieved a sensitivity of 91%. The specificity of KNN was 99%.
Źródło:: Computer Assisted Methods in Engineering and Science; 2023, 30, 2; 247-256
2299-3649
Pojawia się w:: Computer Assisted Methods in Engineering and Science
Dostawca treści:: Biblioteka Nauki

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