Strategic Short Note: Application of Smart Machine Vision in Agriculture, Forestry, Fishery, and Animal Husbandry
IoT and AI in Agriculture: Self-sufficiency in Food Production to Achieve Society 5.0 and SDG’s Globally, Page: 125-131
2023
- 1Citations
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations1
- Citation Indexes1
Book Chapter Description
Food production is an increasingly important topic worldwide due to factors such as population increase and workforce aging. In conventional agriculture, which consists of forestry, fishery, and agriculture, and animal husbandry, manual observation is the main method used by farmers to monitor field and animal conditions. However, the younger generation is reluctant to engage in farming due to the high labor requirements and low wages. To solve this problem, smart machine vision, which is the combination of deep learning and machine vision, is applied for managing farms and increasing production. In this section, the architectures of smart machine vision applications are highlighted. Several examples of the applications are shown.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85207988610&origin=inward; http://dx.doi.org/10.1007/978-981-19-8113-5_8; https://link.springer.com/10.1007/978-981-19-8113-5_8; https://dx.doi.org/10.1007/978-981-19-8113-5_8; https://link.springer.com/chapter/10.1007/978-981-19-8113-5_8
Springer Science and Business Media LLC
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