A Deep Review On Skin Cancer Through Deep Residual Networks

Deep Learning based techniques have being used in medical image analysis to improve classification accuracy in the last few years. Deep Learning Designs such as R-CNN, Fast R-CNN, Faster R-CNN and YOLO have been developed for medical image analysis. Currently, many research studies are going to dete...

Full description

Saved in:
Bibliographic Details
Published in2021 4th International Conference on Computing and Communications Technologies (ICCCT) pp. 464 - 468
Main Authors Gomathi, S., Sudhakar, S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 16.12.2021
Subjects
Deep learning
DeepLearning
FasterR-CNN
FastR-CNN
Image analysis
Melanoma
R-CNN
Residual Neural Networks
Skin
Transfer learning
Visualization
Wounds
YOLO
Online AccessGet full text
DOI10.1109/ICCCT53315.2021.9711808

Cover

More Information
Summary:Deep Learning based techniques have being used in medical image analysis to improve classification accuracy in the last few years. Deep Learning Designs such as R-CNN, Fast R-CNN, Faster R-CNN and YOLO have been developed for medical image analysis. Currently, many research studies are going to detect early skin cancer using transfer learning based Residual Networks. This Paper discusses the various Residual Network based models to detect skin cancer with their implementation, comparison of classification parameters and the strength and challenges in the existing models.
DOI:10.1109/ICCCT53315.2021.9711808