Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{168081,
        author = {V. Arockia Mary Epsy and Dr. P. Radha},
        title = {PEST INSECT DETECTION USING CONVOLUTIONAL NEURAL NETWORK},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {4},
        pages = {1297-1304},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=168081},
        abstract = {Pest insect detection is critical for effective crop management and sustainable agriculture. Traditional methods of pest control often rely on manual inspection, which is time-consuming, labor-intensive, and prone to errors. This paper explores the application of Convolutional Neural Networks (CNN) for automated pest insect detection. CNNs, with their deep learning architecture, are well-suited for image recognition tasks and offer the potential for high accuracy in identifying and classifying various insect species. By training a CNN on a dataset of pest images, the system can automatically detect and classify pests in real-time, helping to reduce pesticide use and improve crop yield. The proposed model is evaluated on its accuracy, precision, and recall, demonstrating its effectiveness in identifying a range of pest species. The results show that CNN-based pest detection systems can significantly enhance agricultural productivity and pest management practices by offering a scalable, automated solution that minimizes human intervention. However, challenges such as data availability, environmental variations, and model generalization remain key areas for further research.},
        keywords = {Convolutional Neural Networks, Model Generalization, Pest Classification, Pest Detection, Sustainable Agriculture},
        month = {September},
        }