A Novel Hybrid Technique for Detecting and Classifying Hyperspectral Images of Tomato Fungal Diseases Based on Deep Feature Extraction and Manhattan Distance
Accurate and early detection of plant diseases is essential for effective management and the advancement of sustainable smart agriculture. However, building large annotated datasets for disease classification is often costly and time-consuming, requiring expert input. To address this challenge, this...
Saved in:
| Main Authors: | Guifu Ma, Seyed Mohamad Javidan, Yiannis Ampatzidis, Zhao Zhang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/14/4285 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Domain-Invariant Few-Shot Contrastive Learning for Hyperspectral Image Classification
by: Wenchen Chen, et al.
Published: (2024-11-01) -
Weighted Contrastive Prototype Network for Few-Shot Hyperspectral Image Classification with Noisy Labels
by: Dan Zhang, et al.
Published: (2024-09-01) -
Hybrid attentive prototypical network for few-shot action recognition
by: Zanxi Ruan, et al.
Published: (2024-08-01) -
Simplified Machine Learning Model as an Intelligent Support for Safe Urban Cycling
by: Alejandro Hernández-Herrera, et al.
Published: (2025-01-01) -
Generative Adversarial Network for Imitation Learning from Single Demonstration
by: Tho Nguyen Duc, et al.
Published: (2021-12-01)