Hybrid Deep Learning Technique for Automated Disease Diagnosis Using Crow Search Optimization (CSO) With Oppositional Learning (OL)

Authors

  • Rahul Kumar, Rajeev Paulus

Keywords:

Hybrid deep learning, Crow Search Optimization (CSO), Oppositional Learning (OL), automated disease diagnosis, precision agriculture, metaheuristic algorithms, Modified ResNet-39, bio-inspired computing.

Abstract

Intelligent, automated systems able to execute diseases diagnosis at very high levelare increasingly called for in precision agriculture. This research suggests a novel hybrid deeplearning system that combines Crow Search Optimization (CSO) and Oppositional Learning

References

Zhang, C., & Liu, Y. (2021). Wavelet transform in noise reduction and signal processing: A review. Signal Processing, 183, 107941.

Johnson, I., & Spence, M. (2019). The molecular probes handbook: A guide to fluorescent probes and labeling technologies (11th ed.). Life Technologies Corporation.

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Published

2024-05-08

How to Cite

Rahul Kumar, Rajeev Paulus. (2024). Hybrid Deep Learning Technique for Automated Disease Diagnosis Using Crow Search Optimization (CSO) With Oppositional Learning (OL). Journal of Computational Analysis and Applications (JoCAAA), 33(05), 1726–1745. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/2650

Issue

Vol. 33 No. 05 (2024): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.