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Detection of fall armyworm (spodoptera frugiperda) in field crops based on mask R-CNN

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Abstract

Nowadays, people are more concerned about the requirement of good quality food and healthier food. Hence, the food manufacturing and processing industries showed their interest in Artificial Intelligence (AI) and Machine Learning (ML) technologies for improving the food quality in major crops and plants. AI and ML are applied in agriculture sectors to protect the field crops from pest attacks. The Fall Armyworm (FAW) is one of the most devastating insects that cause a severe infestation in important field crops to reduce the crop yield. The manual inspection of FAW insects is critical when dealing with similar insects such as corn borer, armyworm, and corn earworm. In this work, FAW insect detection system based on Mask Region Convolutional Neural Network (Mask R-CNN) was proposed to detect the FAW insects and ensure crop quality and safety. The FAW insect dataset is pre-processed, augmented, and annotated to train the Mask R-CNN model. The outcome of the Mask R-CNN detection model was compared with Region CNN (R-CNN), Faster R-CNN, RetinaNet, and Single Shot Multi-box Detector (SSD). The FAW insect detection results showed that the mean average precision of 94.21% was observed in the Mask R-CNN model with the Resnet-101 backbone which proves the effectiveness of the model for instance segmentation of FAW insects in the field crops.

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Acknowledgements

Author K. Thenmozhi acknowledges to Department of Science and Technology, India, for financial support of the work under women scientist scheme B, Grant Number: DST/Disha/SoRF-PM/059/2013. The authors also gratefully acknowledge infrastructural supports from Department of Computer Applications, National Institute of Technology, Tiruchirappalli, India.

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  1. Department of Computer Applications, Machine Learning and Data Analytics Lab, Centre of Excellence in Artificial Intelligence, National Institute of Technology, Tiruchirappalli, 620015, Tamil Nadu, India

    Thenmozhi Kasinathan & Srinivasulu Reddy Uyyala

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  1. Thenmozhi Kasinathan
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  2. Srinivasulu Reddy Uyyala
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Correspondence to Thenmozhi Kasinathan.

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Kasinathan, T., Uyyala, S.R. Detection of fall armyworm (spodoptera frugiperda) in field crops based on mask R-CNN. SIViP 17, 2689–2695 (2023). https://doi.org/10.1007/s11760-023-02485-3

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