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A survey on computer vision approaches for automated classification of skin diseases
Skin diseases are a significant concern for public health, demanding accurate diagnosis for
effective treatment. However, traditional diagnostic methods often suffer from subjectivity …
effective treatment. However, traditional diagnostic methods often suffer from subjectivity …
Evidence-based management of cutaneous scarring in dermatology part 2: Atrophic acne scarring
EY Kim, JH Wong, A Hussain… - Archives of Dermatological …, 2023 - Springer
Atrophic acne scars are the most common type of acne scars and are classified into three
main types: icepick, boxcar, and rolling scars. Various procedures and techniques for …
main types: icepick, boxcar, and rolling scars. Various procedures and techniques for …
[HTML][HTML] A hybrid Grasshopper optimization algorithm for skin lesion segmentation and melanoma classification using deep learning
Skin cancer can be detected through visual examination and confirmed through
dermoscopic analysis and various diagnostic tests. This is because visual observation …
dermoscopic analysis and various diagnostic tests. This is because visual observation …
High performing facial skin problem diagnosis with enhanced mask r-cnn and super resolution gan
M Kim, MH Song - Applied Sciences, 2023 - mdpi.com
Facial skin condition is perceived as a vital indicator of the person's apparent age, perceived
beauty, and degree of health. Machine-learning-based software analytics on facial skin …
beauty, and degree of health. Machine-learning-based software analytics on facial skin …
A novel automatic acne detection and severity quantification scheme using deep learning
J Wang, C Wang, Z Wang, AH Hounye, Z Li… - … Signal Processing and …, 2023 - Elsevier
Accurate detection and severity quantification of acne are of great significance in the precise
treatment of patients. Due to the similar appearance of acne with close severity, it is …
treatment of patients. Due to the similar appearance of acne with close severity, it is …
Perbandingan Kemampuan Klasifikasi Citra X-ray Paru-paru menggunakan Transfer Learning ResNet-50 dan VGG-16
T Berliani, E Rahardja… - Journal of Medicine and …, 2023 - journal.maranatha.edu
Di masa pandemi Covid-19, foto rontgen menjadi umum digunakan untuk memeriksa
pasien diduga Covid-19. Pada citra x-ray paru-paru yang terkena Covid-19 ditemukan …
pasien diduga Covid-19. Pada citra x-ray paru-paru yang terkena Covid-19 ditemukan …
Few-Shot Classification with Multiscale Feature Fusion for Clinical Skin Disease Diagnosis
T Chen, Q Liu, J Yang - Clinical, cosmetic and investigational …, 2024 - Taylor & Francis
Introduction Skin disease is one of the most common diseases and can affect people of all
ages and races. However, the diagnosis of skin diseases via observation is a highly …
ages and races. However, the diagnosis of skin diseases via observation is a highly …
Severity level prediction of acne using hybrid MOA-FCM segmentation algorithm with ANN classifier
P Pandit, M Chavan - Progress in Artificial Intelligence, 2024 - Springer
A person needs self-confidence in order to act normal as well as desired manner. Physical
state of an individual, which sorts feelings of inadequacy and melancholy, which is one of …
state of an individual, which sorts feelings of inadequacy and melancholy, which is one of …
SS-ALDL: Consistency-based semi-supervised label distribution learning for acne severity classification
W Liu, L Zhang, J Zhang, J Li, J Wang, X Jiang - Applied Soft Computing, 2024 - Elsevier
Acne vulgaris is a common skin disease among adolescents. Accurate classification of acne
severity is critical to patient treatment. Most existing acne severity classification models …
severity is critical to patient treatment. Most existing acne severity classification models …
Comprehensive facial acne classification: CNN-SVM synergy
A new framework for automatically detecting and diagnosing facial acne is presented in this
paper. The approach makes use of convolutional neural networks (CNNs) and support …
paper. The approach makes use of convolutional neural networks (CNNs) and support …