Smart farm refers to a farm that can remotely and automatically maintain proper growth and management of crops and livestock by integrating technology with agriculture. Currently, smart farms are concentrated in the field of smart horticulture, and although spreading research is being conducted in limited spaces. In addition, it is difficult to obtain a sufficient amount of data to be used for learning, and there is a problem that data imbalance occurs because it is difficult to obtain a similar amount for each class. In this paper, we propose a method to amplify a small amount of data and to solve the problems of imbalance data by using a feature that can learn to mimic the data of a generative adversarial network. The proposed method can create dataset of various crops and also show high hit rate. Dataset generated from crops would be used to solve problems of data imbalance by learning.
Collaboration network of the authors
16 authors ·
27 co-authorship links
· 5 across different organisations
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Pai Chai University
Korea Institute of Science & Technology Information
Korea University
Kyungbok University
Korea Water Resources Corporation (South Korea)
Affiliation unknown
Different organisations
Same organisation
Affiliation unknown
Thicker line = more joint articles · bigger circle = more articles
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