An ensemble learning integration of multiple CNN with improved vision transformer models for pest classification
- 5 October 2022
- journal article
- research article
- Published by Wiley in Annals of Applied Biology
- Vol. 182 (2), 144-158
- https://doi.org/10.1111/aab.12804
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (61672338, 61873160)
- Natural Science Foundation of Shanghai (21ZR1426500)
This publication has 31 references indexed in Scilit:
- Applications of artificial neural networks in health care organizational decision-making: A scoping reviewPLOS ONE, 2019
- Multi-level learning features for automatic classification of field crop pestsComputers and Electronics in Agriculture, 2018
- Genetic AlgorithmPublished by Springer Science and Business Media LLC ,2018
- Deep learning based classification for paddy pests & diseases recognitionPublished by Association for Computing Machinery (ACM) ,2018
- Pest identification via deep residual learning in complex backgroundComputers and Electronics in Agriculture, 2017
- Densely Connected Convolutional NetworksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2017
- Localization and Classification of Paddy Field Pests using a Saliency Map and Deep Convolutional Neural NetworkScientific Reports, 2016
- Automatic classification for field crop insects via multiple-task sparse representation and multiple-kernel learningComputers and Electronics in Agriculture, 2015
- Speeded-Up Robust Features (SURF)Computer Vision and Image Understanding, 2008
- SURF: Speeded Up Robust FeaturesLecture Notes in Computer Science, 2006