A two‐stream deep neural network‐based intelligent system for complex skin cancer types classification
M Attique Khan, M Sharif, T Akram… - … Journal of Intelligent …, 2022 - Wiley Online Library
Medical imaging systems installed in different hospitals and labs generate images in bulk,
which could support medics to analyze infections or injuries. Manual inspection becomes …
which could support medics to analyze infections or injuries. Manual inspection becomes …
MSRNet: multiclass skin lesion recognition using additional residual block based fine-tuned deep models information fusion and best feature selection
Cancer is one of the leading significant causes of illness and chronic disease worldwide.
Skin cancer, particularly melanoma, is becoming a severe health problem due to its rising …
Skin cancer, particularly melanoma, is becoming a severe health problem due to its rising …
SkinNet‐ENDO: Multiclass skin lesion recognition using deep neural network and Entropy‐Normal distribution optimization algorithm with ELM
The early diagnosis of skin cancer through clinical methods reduces the human mortality
rate. The manual screening of dermoscopic images is not an efficient procedure; therefore …
rate. The manual screening of dermoscopic images is not an efficient procedure; therefore …
Improving skin-disease classification based on customized loss function combined with balanced mini-batch logic and real-time image augmentation
Skin cancer is one of the most common cancers in the world. However, the disease is
curable if detected in the beginning stage. Early detection of malignant lesions through …
curable if detected in the beginning stage. Early detection of malignant lesions through …
Performance Enhancement of Skin Cancer Classification Using Computer Vision
A Magdy, H Hussein, RF Abdel-Kader… - IEEE …, 2023 - ieeexplore.ieee.org
Nowadays, computer vision plays an essential role in disease detection, computer-aided
diagnosis, and patient risk identification. This is especially true for skin cancer, which can be …
diagnosis, and patient risk identification. This is especially true for skin cancer, which can be …
A multi-class skin Cancer classification using deep convolutional neural networks
Skin Cancer accounts for one-third of all diagnosed cancers worldwide. The prevalence of
skin cancers have been rising over the past decades. In recent years, use of dermoscopy …
skin cancers have been rising over the past decades. In recent years, use of dermoscopy …
[HTML][HTML] A deep neural network using modified EfficientNet for skin cancer detection in dermoscopic images
Artificial intelligence (AI) systems can assist in analyzing medical images and aiding in the
early detection of diseases. AI can also ensure the quality of services by avoiding …
early detection of diseases. AI can also ensure the quality of services by avoiding …
Multiclass skin lesion classification using hybrid deep features selection and extreme learning machine
The variation in skin textures and injuries, as well as the detection and classification of skin
cancer, is a difficult task. Manually detecting skin lesions from dermoscopy images is a …
cancer, is a difficult task. Manually detecting skin lesions from dermoscopy images is a …
Skin lesion analyser: an efficient seven-way multi-class skin cancer classification using MobileNet
SS Chaturvedi, K Gupta, PS Prasad - Advanced machine learning …, 2021 - Springer
Skin cancer is an emerging global health problem with 123,000 melanoma and 3,000,000
non-melanoma cases worldwide each year. The recent studies have reported excessive …
non-melanoma cases worldwide each year. The recent studies have reported excessive …
[HTML][HTML] Multiclass skin cancer classification using EfficientNets–a first step towards preventing skin cancer
Skin cancer is one of the most prevalent and deadly types of cancer. Dermatologists
diagnose this disease primarily visually. Multiclass skin cancer classification is challenging …
diagnose this disease primarily visually. Multiclass skin cancer classification is challenging …