A multi-stage melanoma recognition framework with deep residual neural network and hyperparameter optimization-based decision support in dermoscopy images
This paper developed a novel melanoma diagnosis model from dermoscopy images using a
novel hybrid model. Melanoma is the most dangerous and rarest type of skin cancer. It is …
novel hybrid model. Melanoma is the most dangerous and rarest type of skin cancer. It is …
[HTML][HTML] Melanoma classification using a novel deep convolutional neural network with dermoscopic images
Automatic melanoma detection from dermoscopic skin samples is a very challenging task.
However, using a deep learning approach as a machine vision tool can overcome some …
However, using a deep learning approach as a machine vision tool can overcome some …
Deep learning in skin lesion analysis for malignant melanoma cancer identification
MS Sivakumar, LM Leo, T Gurumekala… - Multimedia Tools and …, 2024 - Springer
The higher rate of skin diseases caused by infections, allergies, lifestyle changes, increased
use of chemicals, unhealthy food habits, and hereditary reactions, among other factors …
use of chemicals, unhealthy food habits, and hereditary reactions, among other factors …
Deep learning, sparse coding, and SVM for melanoma recognition in dermoscopy images
This work presents an approach for melanoma recognition in dermoscopy images that
combines deep learning, sparse coding, and support vector machine (SVM) learning …
combines deep learning, sparse coding, and support vector machine (SVM) learning …
[HTML][HTML] Comparative Analysis of Melanoma Classification Using Deep Learning Techniques on Dermoscopy Images
JP Jeyakumar, A Jude, AG Priya Henry, J Hemanth - Electronics, 2022 - mdpi.com
Melanoma is developed due to disturbances in the melanocytes of the skin cells. Every
human skin color is defined by melanin, which is produced by melanocytes. Around the …
human skin color is defined by melanin, which is produced by melanocytes. Around the …
[HTML][HTML] Melanoma diagnosis using deep learning techniques on dermatoscopic images
MF Jojoa Acosta, LY Caballero Tovar… - BMC Medical …, 2021 - Springer
Background Melanoma has become more widespread over the past 30 years and early
detection is a major factor in reducing mortality rates associated with this type of skin cancer …
detection is a major factor in reducing mortality rates associated with this type of skin cancer …
Detection of melanoma in dermoscopic images by integrating features extracted using handcrafted and deep learning models
P Bansal, R Garg, P Soni - Computers & industrial engineering, 2022 - Elsevier
Melanoma is amongst the most aggressive form of skin cancer. The manual detection of
melanoma using dermoscopic images is a labor-intensive and time-consuming process …
melanoma using dermoscopic images is a labor-intensive and time-consuming process …
[HTML][HTML] 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 …
Skin lesions classification based on deep learning approach
As one kind of skin cancer, melanoma is very dangerous. Dermoscopy-based early
detection and reorganization strategy is critical for melanoma therapy. Skin imaging is …
detection and reorganization strategy is critical for melanoma therapy. Skin imaging is …
[HTML][HTML] A comprehensive evaluation and benchmarking of convolutional neural networks for melanoma diagnosis
Simple Summary Melanoma is the most dangerous type of skin cancer. It grows quickly and
has the ability to spread to any organ. This study aims to evaluate and benchmark deep …
has the ability to spread to any organ. This study aims to evaluate and benchmark deep …