Cotton Disease Detection Based on ConvNeXt and Attention Mechanisms
Author:
Affiliation:
1. College of Control Science and Engineering, Zhejiang University, Hangzhou, China
2. Ningbo Innovation Center, Zhejiang University, Ningbo, China
3. Polytechnic Institute, Zhejiang University, Hangzhou, China
Funder
National Key Research and Development Plan
Ningbo Science and Technology Innovation 2025 Major Project
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Networks and Communications,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/7433271/9663041/09893111.pdf?arnumber=9893111
Reference19 articles.
1. Swin-Transformer Based Classification for Rice Diseases Recognition
2. Multi-object tracking using Deep SORT and modified CenterNet in cotton seedling counting
3. A ConvNet for the 2020s
4. RIC-Net: A plant disease classification model based on the fusion of Inception and residual structure and embedded attention mechanism
5. Lightweight dense-scale network (LDSNet) for corn leaf disease identification
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