Title: A novel multigrade classification in FL using brain MRI images based on FHAT_EfficientNet

Authors: Madan Lal Saini; Aravapalli Rama Satish; Telu Venkata Madhusudhana Rao; Jyothi Mandala; Smritilekha Das; Cristin Rajan

Addresses: Department of Computer Science and Engineering, Chandigarh University, Gharuan, Mohali, 140055, Punjab, India ' School of Computer Science and Engineering, VIT-AP University, Andhra Pradesh, India ' Department of AI&DS, Vignan's Institute of Information Technology, Visakhapatnam, 530049, India ' Department of Computer Science and Engineering, Christ (Deemed to be University), Bangalore, India ' Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India ' Department of Computer Science and Engineering, GMR Institute of Technology, Rajam, 532127, Andhra Pradesh, India

Abstract: This paper establishes the fractional harmony artificial tree (FHAT)_EfficientNet for multi-grade classification in federated learning (FL). Here, the established FHAT is attained by the integration of the fractional calculus (FC) and harmony search-based feedback artificial tree (HSFAT) algorithm, and the HSFAT is developed by the combination of harmony search (HS) and feedback artificial tree (FAT). Initially, the input MRI image is taken from a particular dataset and subjected to pre-processing. Thereafter, tumour segmentation is accomplished based on fuzzy local information c-means (FLICM). Later, image augmentation and feature extraction are performed. Finally, the multi-grade classification is carried out using EfficientNet fine-tuned based on the proposed FHAT. Moreover, the established FHAT_EfficientNet attained better accuracy, specificity, sensitivity, mean squared error (MSE), root mean square error (RMSE), and loss function of 0.917, 0.936, 0.966, 0.058, 0.241, and 0.083.

Keywords: EfficientNet; fuzzy local information c-means; FLICM; federated learning; fractional harmony artificial tree; FHAT; fractional calculus.

DOI: 10.1504/IJAHUC.2025.147753

International Journal of Ad Hoc and Ubiquitous Computing, 2025 Vol.49 No.4, pp.251 - 269

Received: 02 Apr 2024
Accepted: 15 Nov 2024
Published online: 30 Jul 2025 *

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