GLNet: global-local feature network for wheat leaf disease image classification
Addressing the issues with insufficient multi-scale feature perception and incomplete understanding of global information in traditional convolutional neural networks for image classification of wheat leaf disease, this paper proposes a global local feature network, i.e. GLNet, which adopts a unique...
Saved in:
| Main Authors: | Shangze Li, Shen Liu, Mingyu Ji, Yuhao Cao, Bai Yun |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2024-12-01
|
| Series: | Frontiers in Plant Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fpls.2024.1471705/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Plant leaf classification using the multiscale entropy of curvature and feature aggregation
by: Raphael G. Pinheiro, et al.
Published: (2025-11-01) -
PLANT CLASSIFICATION BASED ON LEAF EDGES AND LEAF MORPHOLOGICAL VEINS USING WAVELET CONVOLUTIONAL NEURAL NETWORK
by: Wulan Dewi, et al.
Published: (2021-03-01) -
Multi-Stage Neural Network-Based Ensemble Learning Approach for Wheat Leaf Disease Classification
by: Samia Nawaz Yousafzai, et al.
Published: (2025-01-01) -
Investigating the Impact of Sowing Date on Wheat Leaf Morphology Through Image Analysis
by: Junfan Chen, et al.
Published: (2025-04-01) -
A Feature Dynamic Enhancement and Global Collaboration Guidance Network for Remote Sensing Image Compression
by: Q. Z. Fang, et al.
Published: (2025-06-01)