An ensemble model of convolution and recurrent neural network for skin disease classification-Reference-Cited by-同舟云学术

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An ensemble model of convolution and recurrent neural network for skin disease classification

Published:2021-10-28 Issue:1 Volume:32 Page:218-229
ISSN:0899-9457
Container-title:International Journal of Imaging Systems and Technology
language:en
Short-container-title:Int J Imaging Syst Tech

Author:

Ahmad Belal¹^ORCID,Usama Mohd²,Ahmad Tanvir³,Khatoon Shabnam⁴,Alam Chaudhary Maqbool¹

Affiliation:

1. School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

2. Department of Computer Science and Technology Kalasalingam Academy of Research and Education Srivilliputhur India

3. School of Computer Science and Technology North China Electric Power University Beijing China

4. School of Management Science and Engineering China University of Geosciences Wuhan China

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Software,Electronic, Optical and Magnetic Materials

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ima.22661

Reference46 articles.

1. StomachNet: Optimal Deep Learning Features Fusion for Stomach Abnormalities Classification

2. Skin Lesion Segmentation and Multiclass Classification Using Deep Learning Features and Improved Moth Flame Optimization

3. Occlusion Aware Facial Expression Recognition Using CNN With Attention Mechanism

4. Microscopic brain tumor detection and classification using 3D CNN and feature selection architecture

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2. A region of interest focused Triple UNet architecture for skin lesion segmentation;International Journal of Imaging Systems and Technology;2024-05

3. A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Skin Cancer Detection and Classification: Exploring Performance Across Multiple Parameters;2024 3rd International Conference on Sentiment Analysis and Deep Learning (ICSADL);2024-03-13

4. Recent Advancements and Perspectives in the Diagnosis of Skin Diseases Using Machine Learning and Deep Learning: A Review;Diagnostics;2023-11-22

5. An in-depth analysis of Convolutional Neural Network architectures with transfer learning for skin disease diagnosis;Healthcare Analytics;2023-11

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