Detection and Recognition of the Invasive species, Hylurgus ligniperda, in Traps, Based on a Cascaded Convolution Neural Network,Pest Management Science

当前位置： X-MOL 学术 › Pest Manag. Sci. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Detection and Recognition of the Invasive species, Hylurgus ligniperda, in Traps, Based on a Cascaded Convolution Neural Network
Pest Management Science ( IF 4.1 ) Pub Date : 2024-04-17 , DOI: 10.1002/ps.8126
Xiahui Zhang ₁ , Zhengyi Li ₁ , Lili Ren ₁ , Xuanxin Liu ₂ , Tian Zeng ₃ , Jing Tao ₁

Affiliation

Hylurgus ligniperda, an invasive species originating from Eurasia, is now a major forestry quarantine pest worldwide. In recent years, it has caused significant damage in China. While traps have been effective in monitoring and controlling pests, manual inspections are labor-intensive and require expertise in insect classification. To address this, we applied a two-stage cascade convolutional neural network, YOLOX-MobileNetV2 (YOLOX-Mnet), for identifying H. ligniperda and other pests captured in traps. This method streamlines target and non-target insect detection from trap images, offering a more efficient alternative to manual inspections.

更新日期：2024-04-17

点击分享查看原文

点击收藏

阅读更多本刊最新论文本刊介绍/投稿指南

全部期刊列表>>