Pest-ConFormer: A hybrid CNN-Transformer architecture for large-scale multi-class crop pest recognition-Reference-Cited by-同舟云学术

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Pest-ConFormer: A hybrid CNN-Transformer architecture for large-scale multi-class crop pest recognition

Published:2024-12 Issue: Volume:255 Page:124833
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Fang Mingwei^ORCID,Tan Zhiping^ORCID,Tang Yu^ORCID,Chen Weizhao^ORCID,Huang Huasheng^ORCID,Dananjayan Sathian^ORCID,He Yong^ORCID,Luo Shaoming^ORCID

Publisher

Elsevier BV

Reference53 articles.

1. Cotton pests classification in field-based images using deep residual networks;Alves;Computers and Electronics in Agriculture,2020

2. Crop pest classification with a genetic algorithm-based weighted ensemble of deep convolutional neural networks;Ayan;Computers and Electronics in Agriculture,2020

3. Genetic algorithm-based hyperparameter optimization for convolutional neural networks in the classification of crop pests;Ayan;Arabian Journal for Science and Engineering,2024

4. Crop pest recognition using attention-embedded lightweight network under field conditions;Chen;Applied Entomology and Zoology,2021

5. Pest identification via deep residual learning in complex background;Cheng;Computers and Electronics in Agriculture,2017

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