Perfomance comparision on the PAD dataset.

<div><p>Skin cancer is rapidly growing globally. In the past decade, an automated diagnosis system has been developed using image processing and machine learning. The machine learning methods require hand-crafted features, which may affect performance. Recently, a convolution neural netw...

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Bibliographic Details
Main Author:	Dhirendra Prasad Yadav (20235097) (author)
Other Authors:	Bhisham Sharma (20235100) (author), Shivank Chauhan (20235106) (author), Julian L. Webber (20235103) (author), Abolfazl Mehbodniya (11988747) (author)
Published:	2024
Subjects:	Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified rapidly growing globally lightweight transformer encoder convolution neural network automated diagnosis system model obtained 94 model &# 8217 different patch sizes scale lightweight cross diagnose skin cancer different scales improved may affect performance ham 10000 dataset dimensional spatial features provides global attention ham 10000 spatial features model superiority different parts skin lesion performed cross global attention extracted features enhanced features crafted features precision values past decade pad datasets machine learning fusion strategy dermoscopic images cnn improved based methods
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Perfomance comparision on the PAD dataset.

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