- Title
- Plant disease detection and classification for farmers and everyday gardeners
- Creator
- Poole, Louise C, Brown, Dane L
- Subject
- To be catalogued
- Date
- 2019
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/465722
- Identifier
- vital:76635
- Identifier
- xlink:href="https://www.researchgate.net/profile/Dane-Brown-2/publication/335378684_Plant_Disease_Detection_and_Classification_for_Farmers_and_Everyday_Gardeners/links/5d611905299bf1f70b090b54/Plant-Disease-Detection-and-Classification-for-Farmers-and-Everyday-Gardeners.pdf"
- Description
- Identifying and rating diseases by hand is an expensive, time consuming, subjective and unreliable method as compared to what computers can provide. Image processing and machine learning enable automated disease identification. Research has proven that automated disease identification systems can be used as a preventative measure against plant rot and death. This paper narrows down the best techniques to segment images of leaves toward improved classification of diseases found on those leaves. An investigation is conducted on image segmentation and machine learning techniques, including state-of-the-art systems, to determine the most appropriate approach to prevent death and rot in plants. Promising results were observed during testing, and show that a system can be implemented to assist with plant health that is relevant to both home gardeners and farmers.
- Format
- computer, online resource, application/pdf, 1 online resource (5 pages), pdf
- Publisher
- Southern Africa Telecommunication Networks and Applications Conference (SA TNAC)
- Language
- English
- Relation
- Poole, L. and Brown, D., Plant disease detection and classification for farmers and everyday gardeners. In 22nd Southern Africa Telecommunication Networks and Applications Conference (SATNAC) (pp. 282-287), Poole, L. and Brown, D., Plant disease detection and classification for farmers and everyday gardeners. In 22nd Southern Africa Telecommunication Networks and Applications Conference (SATNAC) (pp. 282-287) p. 282 2019
- Rights
- Publisher
- Rights
- Use of this resource is governed by the terms and conditions of Southern Africa Telecommunication Networks and Applications Conference (SA TNAC) Statement (https://www.satnac.org.za/)
- Rights
- Open Access
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- Visitors: 33
- Downloads: 0
Collections
Brown, Dane A (Dr)
RU Department of Computer Science
SDG 09. Industry, Innovation and Infrastructure
SDG 15. Life On Land
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details | SOURCE1 | Plant disease detection and classification for farmers and everyday gardeners.pdf | 748 KB | Adobe Acrobat PDF | View Details |