A novel Deeplabv3+ and vision-based transformer model for segmentation and classification of skin lesions-Reference-Cited by-同舟云学术

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A novel Deeplabv3+ and vision-based transformer model for segmentation and classification of skin lesions

Published:2024-06 Issue: Volume:92 Page:106084
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Ahmad Iqra,Amin Javaria,IkramUllah Lali Muhammad,Abbas Farhat,Imran Sharif Muhammad

Publisher

Elsevier BV

Reference65 articles.

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2. Comparison of segmentation methods for melanoma diagnosis in dermoscopy images;Silveira;IEEE J. Sel. Top. Signal Process.,2009

3. Diagnostic accuracy of dermoscopy;Kittler;Lancet Oncol.,2002

4. Skin lesion classification of dermoscopic images using machine learning and convolutional neural network;Shetty;Sci. Rep.,2022

5. Skin cancer segmentation with the aid of multi-class dilated D-net (MD2N) framework;Kumar;Multimed. Tools Appl.,2023

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. RvXmBlendNet: A Multi-architecture Hybrid Model for Improved Skin Cancer Detection;Human-Centric Intelligent Systems;2024-09-09

2. YoTransViT: A transformer and CNN method for predicting and classifying skin diseases using segmentation techniques;Informatics in Medicine Unlocked;2024

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