Deep Learning Techniques for the Automatic Detection and Classification of Rice Diseases-Reference-Cited by-同舟云学术

Deep Learning Techniques for the Automatic Detection and Classification of Rice Diseases

Published:2023 Issue: Volume: Page:229-240
ISSN:2367-3370
Container-title:Information and Communication Technology for Competitive Strategies (ICTCS 2022)
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Author:

Paul Bijan^ORCID,Rozario Raj Xavier^ORCID,Roy Aditi^ORCID,Chakma Siddharth^ORCID,Wohra Mohammad Abrar Abedin^ORCID,Mahmud Khan Raqib^ORCID,Rahman Mohammed Ashikur^ORCID

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-9638-2_20

Reference20 articles.

1. Bangladesh GDP from Agriculture (2019) https://tradingeconomics.com/bangladesh/gdp-from-agriculture. Last accessed 25 Aug 2019

2. Akter T, Parvin MT, Mila FA, Nahar A (2019) Factors determining the profitability of rice farming in Bangladesh. J Bangladesh Agric Univ 17(1):86–91

3. USDA (2019) Rice output continues to see growth. https://archive.dhakatribune.com/business/economy/2019/04/09/usda-rice-output-continues-to-see-growth. Last accessed 25 Aug 2019

4. Miah SA, Shahjahan AK, Hossain MA, Sharma NR (1985) A survey of rice diseases in Bangladesh. Trop Pest Manage 31(3):208–213

5. Kaundal R, Kapoor AS, Raghava GPS (2006) Machine learning techniques in disease forecasting: a case study on rice blast prediction. BMC Bioinf 7(1)

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