Adaptive melanoma diagnosis using evolving clustering, ensemble and deep neural networks
In this research, we propose a variant of the Particle Swarm Optimization (PSO) algorithm,
namely hybrid learning PSO (HLPSO), for skin lesion segmentation and classification …
namely hybrid learning PSO (HLPSO), for skin lesion segmentation and classification …
Transfer learning without knowing: Reprogramming black-box machine learning models with scarce data and limited resources
Current transfer learning methods are mainly based on finetuning a pretrained model with
target-domain data. Motivated by the techniques from adversarial machine learning (ML) …
target-domain data. Motivated by the techniques from adversarial machine learning (ML) …
An interpretable skin cancer classification using optimized convolutional neural network for a smart healthcare system
Skin cancer is a prevalent form of malignancy globally, and its early and accurate diagnosis
is critical for patient survival. Clinical evaluation of skin lesions is essential, but it faces …
is critical for patient survival. Clinical evaluation of skin lesions is essential, but it faces …
Deep learning in medical imaging: A brief review
S Serte, A Serener, F Al‐Turjman - Transactions on Emerging …, 2022 - Wiley Online Library
Researchers have used deep learning methods for a human level or better disease
identification and detection. This paper reports, in brief, the recent work in deep learning …
identification and detection. This paper reports, in brief, the recent work in deep learning …
Towards automated melanoma detection with deep learning: Data purification and augmentation
Melanoma is one of ten most common cancers in the US. Early detection is crucial for
survival, but often the cancer is diagnosed in the fatal stage. Deep learning has the potential …
survival, but often the cancer is diagnosed in the fatal stage. Deep learning has the potential …
Melanoma segmentation using deep learning with test-time augmentations and conditional random fields
In a computer-aided diagnostic (CAD) system for skin lesion segmentation, variations in
shape and size of the skin lesion makes the segmentation task more challenging. Lesion …
shape and size of the skin lesion makes the segmentation task more challenging. Lesion …
Intelligent skin cancer detection using enhanced particle swarm optimization
In this research, we undertake intelligent skin cancer diagnosis based on dermoscopic
images using a variant of the Particle Swarm Optimization (PSO) algorithm for feature …
images using a variant of the Particle Swarm Optimization (PSO) algorithm for feature …
Computer-aided diagnosis (CAD) system based on multi-layer feature fusion network for skin lesion recognition in dermoscopy images
I Bakkouri, K Afdel - Multimedia Tools and Applications, 2020 - Springer
Skin lesion recognition is one of the most important tasks in dermoscopic image analysis.
Current Convolutional Neural Network (CNN) algorithms based recognition methods tend to …
Current Convolutional Neural Network (CNN) algorithms based recognition methods tend to …
A survey on deep learning for skin lesion segmentation
Skin cancer is a major public health problem that could benefit from computer-aided
diagnosis to reduce the burden of this common disease. Skin lesion segmentation from …
diagnosis to reduce the burden of this common disease. Skin lesion segmentation from …
Melanoma diagnosis using deep learning and fuzzy logic
Melanoma or malignant melanoma is a type of skin cancer that develops when melanocyte
cells, damaged by excessive exposure to harmful UV radiations, start to grow out of control …
cells, damaged by excessive exposure to harmful UV radiations, start to grow out of control …