An towards efficient optimal recurrent neural network-based brian tumour classification using cat and rat swarm (CARS) optimisation-Reference-Cited by-同舟云学术

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An towards efficient optimal recurrent neural network-based brian tumour classification using cat and rat swarm (CARS) optimisation

Published:2023-09-14 Issue: Volume: Page:
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Mactina Josephine Nijofi,S Neduncheliyan

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-023-16870-0.pdf

Reference30 articles.

1. Fasihi, MS, Wasfy BM (2021) Brain tumor grade classification using LSTM neural networks with domain pre-transforms. 2021 IEEE International Midwest Symposium on Circuits and Systems (MWSCAS). IEEE

2. Sethy PK, Behera Santi Kumari (2021) A data constrained approach for brain tumour detection using fused deep features and SVM. Multimedia Tools and Applications 80(19):28745–28760

3. Gumaei A et al (2019) A hybrid feature extraction method with regularised extreme learning machine for brain tumor classification. IEEE Access 7:36266–36273

4. Huang Z et al (2020) Convolutional neural network based on complex networks for brain tumor image classification with a modified activation function. IEEE Access 8:89281–89290

5. Kapila D, Bhagat N (2022) Efficient feature selection technique for brain tumor classification utilising hybrid fruit fly based abc and ann algorithm. Mater Today: Proc 51:12–20

Cited by 1 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. Exploring Deep Learning for Efficient Data Management in Brain Tumor Classification: An Overview;2024 11th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO);2024-03-14

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