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Computer Sciences & Mathematics Forum
Volume 12
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10.3390/cmsf2025012014
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Proceeding Paper

CNN-Based Image Classification of Silkworm for Early Prediction of Diseases †

by
Kajal Mungase
1,*,
Shwetambari Chiwhane
1 and
Priyanka Paygude
2
1
Symbiosis Institute of Technology, Symbiosis International Deemed University, Pune 412115, India
2
Department of Information Technology, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune 411043, India
*
Author to whom correspondence should be addressed.
†
Presented at the First International Conference on Computational Intelligence and Soft Computing (CISCom 2025), Melaka, Malaysia, 26–27 November 2025.
Comput. Sci. Math. Forum 2025, 12(1), 14; https://doi.org/10.3390/cmsf2025012014
Published: 25 December 2025
(This article belongs to the Proceedings of First International Conference on Computational Intelligence and Soft Computing (CISCom 2025))
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Abstract

The need to automate the disease identification processes is frequent because manual identification is time-consuming and needs professional skills to be performed; hence, it may improve effectiveness and precision. This paper has resolved the problem by using image classification with deep learning to detect silkworm diseases. A Kaggle-sourced dataset of work of 492 labelled samples (247 diseased and 245 healthy) was used with a stratified division into 392 training and 100 testing samples. The transfer learning method was performed on two Residual Network models, ResNet-18 and ResNet-50, in which pretrained convolutional layers were frozen and the last fully connected layer was trained to conduct binomial classification. Performance was measured by standard evaluation metrics such as accuracy, precision, recall, F1-score, and confusion matrices.
Keywords: silkworm diseases; deep learning; Res-net18; efficient images classification; sericulture automation silkworm diseases; deep learning; Res-net18; efficient images classification; sericulture automation

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MDPI and ACS Style

Mungase, K.; Chiwhane, S.; Paygude, P. CNN-Based Image Classification of Silkworm for Early Prediction of Diseases. Comput. Sci. Math. Forum 2025, 12, 14. https://doi.org/10.3390/cmsf2025012014

AMA Style

Mungase K, Chiwhane S, Paygude P. CNN-Based Image Classification of Silkworm for Early Prediction of Diseases. Computer Sciences & Mathematics Forum. 2025; 12(1):14. https://doi.org/10.3390/cmsf2025012014

Chicago/Turabian Style

Mungase, Kajal, Shwetambari Chiwhane, and Priyanka Paygude. 2025. "CNN-Based Image Classification of Silkworm for Early Prediction of Diseases" Computer Sciences & Mathematics Forum 12, no. 1: 14. https://doi.org/10.3390/cmsf2025012014

APA Style

Mungase, K., Chiwhane, S., & Paygude, P. (2025). CNN-Based Image Classification of Silkworm for Early Prediction of Diseases. Computer Sciences & Mathematics Forum, 12(1), 14. https://doi.org/10.3390/cmsf2025012014

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