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  1. KRISHI Publication and Data Inventory Repository
  2. Agricultural Education A1
  3. ICAR-Indian Agricultural Statistics Research Institute B7
  4. AEdu-IASRI-Publication
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Please use this identifier to cite or link to this item: http://krishi.icar.gov.in/jspui/handle/123456789/68625
Title: Wheat rust disease identification using deep learning
Other Titles: Not Available
Authors: Sapna Nigam
Rajni Jain
Sudeep Marwaha
Alka Arora
ICAR Data Use Licennce: http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf
Author's Affiliated institute: ICAR::Indian Agricultural Statistics Research Institute
ICAR::National Institute of Agricultural Economics and Policy Research
Published/ Complete Date: 2021-02-08
Project Code: Not Available
Keywords: plant disease
wheat rust
CNN
deep learning
artificial intelligence
Publisher: De Gruyter
Citation: Nigam, S., Jain, R., Marwaha, S., & Arora, A. (2021). 12 Wheat rust disease identification using deep learning. In Internet of Things and Machine Learning in Agriculture (pp. 239-250). De Gruyter.
Series/Report no.: Not Available;
Abstract/Description: Automated image-based tools are required when a human assessment of plant disease identification is expensive, inappropriate, or unreliable. Thus, there is a need to recognize cost-effective automated computational systems and image-based tools for disease detection that would facilitate advancements in agriculture. Deep learning (DL) is a deep neural network that uses multiple levels of abstraction for the hierarchical representation of the data. The convolutional neural network model is used, in this chapter, on 2,000 images to identify the wheat rust disease in an unseen leaf image. The results show that DL has the potential to identify plant diseases with much higher accuracy.
Description: Not Available
ISBN: 9783110691276
9783110691221
Type(s) of content: Book chapter
Sponsors: Not Available
Language: English
Name of Journal: Not Available
Volume No.: Not Available
Page Number: 239-250
Name of the Division/Regional Station: Not Available
Source, DOI or any other URL: https://doi.org/10.1515/9783110691276-012
URI: http://krishi.icar.gov.in/jspui/handle/123456789/68625
Appears in Collections:AEdu-IASRI-Publication

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