Crop pest recognition in natural scenes using convolutional neural networks

Y Li, H Wang, LM Dang, A Sadeghi-Niaraki… - … and Electronics in …, 2020 - Elsevier
Crop diseases and insect pests are major agricultural problems worldwide, because the
severity and extent of their occurrence causes significant crop losses. In addition, traditional …

Automatic greenhouse insect pest detection and recognition based on a cascaded deep learning classification method

DJA Rustia, JJ Chao, LY Chiu, YF Wu… - Journal of applied …, 2021 - Wiley Online Library
Inspection of insect sticky paper traps is an essential task for an effective integrated pest
management (IPM) programme. However, identification and counting of the insect pests …

Adaptive feature fusion pyramid network for multi-classes agricultural pest detection

L Jiao, C Xie, P Chen, J Du, R Li, J Zhang - Computers and electronics in …, 2022 - Elsevier
The accurate and robust crop pest detection system is an important step to enable the
reliable forecasting of agricultural pest in the community of precision agriculture, attracting …

Recognition pest by image‐based transfer learning

W Dawei, D Limiao, N Jiangong, G Jiyue… - Journal of the …, 2019 - Wiley Online Library
BACKGROUND Plant pests mainly refers to insects and mites that harm crops and products.
There are a wide variety of plant pests, with wide distribution, fast reproduction and large …

Improved CNN method for crop pest identification based on transfer learning

Y Liu, X Zhang, Y Gao, T Qu… - Computational intelligence …, 2022 - Wiley Online Library
Timely treatment and elimination of diseases and pests can effectively improve the yield and
quality of crops, but the current identification methods are difficult to achieve efficient and …

A novel multi-label pest image classifier using the modified Swin Transformer and soft binary cross entropy loss

Q Guo, C Wang, D Xiao, Q Huang - Engineering Applications of Artificial …, 2023 - Elsevier
As pests can cause heavy crop losses, integrated pest management is a vital aspect of
agriculture. In general, pest recognition is essential to the integrated pest management …

基于改进EfficientNet 模型的作物害虫识别.

甘雨, 郭庆文, 王春桃, 梁炜健… - Transactions of the …, 2022 - search.ebscohost.com
精准识别作物害虫是控制虫害发生态势的重要基础. 针对现有害虫识别准确率较低,
基于卷积神经网络的害虫识别结构较复杂且计算成本较高, 害虫识别模型泛化能力低及难以部署 …

An intelligent system for high-density small target pest identification and infestation level determination based on an improved YOLOv5 model

L Sun, Z Cai, K Liang, Y Wang, W Zeng… - Expert Systems with …, 2024 - Elsevier
Purpose: A deep learning-based intelligent system has been developed for the identification
and detection of high-density small target pests with the aim of addressing the limitations …

Classification method of significant rice pests based on deep learning

Z Li, X Jiang, X Jia, X Duan, Y Wang, J Mu - Agronomy, 2022 - mdpi.com
Rice pests are one of the main factors affecting rice yield. The accurate identification of pests
facilitates timely preventive measures to avoid economic losses. Some existing open source …

Crop pest image classification based on improved densely connected convolutional network

H Peng, H Xu, Z Gao, Z Zhou, X Tian, Q Deng… - Frontiers in Plant …, 2023 - frontiersin.org
Introduction Crop pests have a great impact on the quality and yield of crops. The use of
deep learning for the identification of crop pests is important for crop precise management …