Optimizing Tumor Classification Through Transfer Learning and Particle Swarm Optimization-Driven Feature Extraction-Reference-Cited by-同舟云学术

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Optimizing Tumor Classification Through Transfer Learning and Particle Swarm Optimization-Driven Feature Extraction

Published:2024 Issue: Volume:12 Page:85929-85939
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Siddique Ali Akbar¹^ORCID,Raza Asif²^ORCID,Alshehri Mohammed S.³^ORCID,Alasbali Nada⁴,Abbasi Saadullah Farooq⁵^ORCID

Affiliation:

1. Department of Telecommunication Engineering, Sir Syed University of Engineering and Technology, Karachi, Pakistan

2. Department of Computer Science, Sir Syed University of Engineering and Technology, Karachi, Pakistan

3. Departments of Computer Science, College of Computer Science and Information Systems, Najran University, Najran, Saudi Arabia

4. Department of Informatics and Computing Systems, Computer Science College, King Khalid University, Abha, Saudi Arabia

5. Department of Electronic, Electrical and System Engineering, University of Birmingham, Birmingham, U.K.

Funder

Deanship of Scientific Research at King Khalid University for funding this work through the Small Group Research Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10552767.pdf?arnumber=10552767

Reference39 articles.

1. Transfer learning using computational intelligence: A survey

2. A Lightweight Deep Learning Based Microwave Brain Image Network Model for Brain Tumor Classification Using Reconstructed Microwave Brain (RMB) Images

3. SSO-RBNN driven brain tumor classification with Saliency-K-means segmentation technique

4. Role of Ensemble Deep Learning for Brain Tumor Classification in Multiple Magnetic Resonance Imaging Sequence Data

5. MobileNetV1-Based Deep Learning Model for Accurate Brain Tumor Classification

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