Plant disease identification using autoencoder
Plant diseases limit the crop production and have received more attention from experts and farmers. Plant disease identification is carried out by experienced people or needs microscopic identification. However, trained people or professionals are not always available, and the manual approach may le...
Saved in:
Main Author: | Ong, Janice Aun Nee |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2021
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/99441/1/JaniceOngAunNeeMKE2021.pdf http://eprints.utm.my/id/eprint/99441/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:149764 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Long short-term memory autoencoder-based anomaly detection system for electric motors
by: Sharrar, Labib
Published: (2022) -
Intrusion detection models using enhanced denoising autoencoders and lightgbm classifier with improved detection performance
by: Sheikh, Abdul Hameed
Published: (2023) -
A novel autoencoder for structural anomalies detection in river tunnel operation
by: Tan, Xu-Yan, et al.
Published: (2024) -
Plant disease severity classification using deep learning
by: Lee, San Kong
Published: (2020) -
Semantic segmentation for plant disease using deep learning
by: Shu, Shi Hao
Published: (2020)