YOLO-PEST: a novel rice pest detection approach based on YOLOv5s [PDF]
Plant MethodsIn rice pest management, accurate pest detection is critical for intelligent agricultural systems, yet challenges like limited dataset availability, pest occlusion, and insufficient small object detection accuracy hinder effective monitoring.
Jun Qiang +5 more
doaj +4 more sources
Crop pest detection by three-scale convolutional neural network with attention. [PDF]
PLoS ONE, 2023 Crop pests seriously affect the yield and quality of crop. To timely and accurately control crop pests is particularly crucial for crop security, quality of life and a stable agricultural economy.
Xuqi Wang +3 more
doaj +3 more sources
Yolo-Pest: An Insect Pest Object Detection Algorithm via CAC3 Module
Sensors, 2023 Insect pests have always been one of the main hazards affecting crop yield and quality in traditional agriculture. An accurate and timely pest detection algorithm is essential for effective pest control; however, the existing approach suffers from a ...
Qiuchi Xiang +5 more
doaj +4 more sources
Prior knowledge auxiliary for few-shot pest detection in the wild [PDF]
Frontiers in Plant Science, 2023 One of the main techniques in smart plant protection is pest detection using deep learning technology, which is convenient, cost-effective, and responsive.
Xiaodong Wang +10 more
doaj +2 more sources
A Novel Deep Learning Model for Accurate Pest Detection and Edge Computing Deployment [PDF]
Insects, 2023 In this work, an attention-mechanism-enhanced method based on a single-stage object detection model was proposed and implemented for the problem of rice pest detection.
Huangyi Kang +7 more
doaj +2 more sources
Feature Refinement Method Based on the Two-Stage Detection Framework for Similar Pest Detection in the Field [PDF]
Insects, 2023 Efficient pest identification and control is critical for ensuring food safety. Therefore, automatic detection of pests has high practical value for Integrated Pest Management (IPM).
Hongbo Chen +7 more
doaj +2 more sources
An efficient feature pyramid network with adaptive LSTM for pest detection and classification in IoT [PDF]
Scientific ReportsCrop pests are a major cause of economic loss and environmental damage globally. Timely detection of pests is crucial for protecting crops and maintaining the global food supply.
Rajasekaran Arunachalam +5 more
doaj +2 more sources
AgriPest-YOLO: A rapid light-trap agricultural pest detection method based on deep learning [PDF]
Frontiers in Plant Science, 2022 Light traps have been widely used for automatic monitoring of pests in the field as an alternative to time-consuming and labor-intensive manual investigations. However, the scale variation, complex background and dense distribution of pests in light-trap
Wei Zhang +5 more
doaj +2 more sources
Deep learning-based rice pest detection research. [PDF]
PLoS OneWith the increasing pressure on global food security, the effective detection and management of rice pests have become crucial. Traditional pest detection methods are not only time-consuming and labor-intensive but also often fail to achieve real-time monitoring and rapid response.
Xiong P, Zhang C, He L, Zhan X, Han Y.
europepmc +5 more sources
Pest Detection in Edible Crops at the Edge: An Implementation-Focused Review of Vision, Spectroscopy, and Sensors [PDF]
SensorsEarly pest detection in edible crops demands sensing solutions that can run at the edge under tight power, budget, and maintenance constraints. This review synthesizes peer-reviewed work (2015–2025) on three modality families—vision/AI, spectroscopy ...
Dennys Jhon Báez-Sánchez +5 more
doaj +2 more sources