Advanced Insect Detection Network for UAV-Based Biodiversity Monitoring DOI Creative Commons
Halimjon Khujamatov, Shakhnoza Muksimova,

Mirjamol Abdullaev

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(6), P. 962 - 962

Published: March 9, 2025

The Advanced Insect Detection Network (AIDN), which represents a significant advancement in the application of deep learning for ecological monitoring, is specifically designed to enhance accuracy and efficiency insect detection from unmanned aerial vehicle (UAV) imagery. Utilizing novel architecture that incorporates advanced activation normalization techniques, multi-scale feature fusion, custom-tailored loss function, AIDN addresses unique challenges posed by small size, high mobility, diverse backgrounds insects images. In comprehensive testing against established models, demonstrated superior performance, achieving 92% precision, 88% recall, an F1-score 90%, mean Average Precision (mAP) score 89%. These results signify substantial improvement over traditional models such as YOLO v4, SSD, Faster R-CNN, typically show performance metrics approximately 10–15% lower across similar tests. practical implications AIDNs are profound, offering benefits agricultural management biodiversity conservation. By automating classification processes, reduces labor-intensive tasks manual enabling more frequent accurate data collection. This collection quality frequency enhances decision making pest conservation, leading effective interventions strategies. AIDN’s design capabilities set new standard field, promising scalable solutions UAV-based monitoring. Its ongoing development expected integrate additional sensory real-time adaptive further applicability, ensuring its role transformative tool monitoring environmental science.

Language: Английский

Advanced Insect Detection Network for UAV-Based Biodiversity Monitoring DOI Creative Commons
Halimjon Khujamatov, Shakhnoza Muksimova,

Mirjamol Abdullaev

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(6), P. 962 - 962

Published: March 9, 2025

The Advanced Insect Detection Network (AIDN), which represents a significant advancement in the application of deep learning for ecological monitoring, is specifically designed to enhance accuracy and efficiency insect detection from unmanned aerial vehicle (UAV) imagery. Utilizing novel architecture that incorporates advanced activation normalization techniques, multi-scale feature fusion, custom-tailored loss function, AIDN addresses unique challenges posed by small size, high mobility, diverse backgrounds insects images. In comprehensive testing against established models, demonstrated superior performance, achieving 92% precision, 88% recall, an F1-score 90%, mean Average Precision (mAP) score 89%. These results signify substantial improvement over traditional models such as YOLO v4, SSD, Faster R-CNN, typically show performance metrics approximately 10–15% lower across similar tests. practical implications AIDNs are profound, offering benefits agricultural management biodiversity conservation. By automating classification processes, reduces labor-intensive tasks manual enabling more frequent accurate data collection. This collection quality frequency enhances decision making pest conservation, leading effective interventions strategies. AIDN’s design capabilities set new standard field, promising scalable solutions UAV-based monitoring. Its ongoing development expected integrate additional sensory real-time adaptive further applicability, ensuring its role transformative tool monitoring environmental science.

Language: Английский

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