Ensemble of weighted deep concatenated features for the skin disease classification model using modified long short term memory-Reference-Cited by-同舟云学术

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Ensemble of weighted deep concatenated features for the skin disease classification model using modified long short term memory

Published:2022-07 Issue: Volume:76 Page:103729
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Elashiri Mohamed A.,Rajesh Arunachalam,Nath Pandey Surya,Kumar Shukla Surendra,Urooj Shabana,Lay-Ekuakille Aime'

Funder

Princess Nourah Bint Abdulrahman University

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing,Biomedical Engineering

Reference41 articles.

1. Progressive Transfer Learning and Adversarial Domain Adaptation for Cross-Domain Skin Disease Classification;Gu;IEEE J. Biomed. Health. Inf.,2020

2. Improving Skin-Disease Classification Based on Customized Loss Function Combined With Balanced Mini-Batch Logic and Real-Time Image Augmentation;Pham;IEEE Access,2020

3. Discriminative Feature Learning for Skin Disease Classification Using Deep Convolutional Neural Network;Ahmad;IEEE Access,2020

4. Robust Skin Disease Classification by Distilling Deep Neural Network Ensemble for the Mobile Diagnosis of Herpes Zoster;Back;IEEE Access,2021

5. Simple-Encoded evolving convolutional neural network and its application to skin disease image classification;He;Swarm Evol. Comput.,2021

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