Abstract
The agricultural sector has a very pivotal role, furthermore very important in the global economy country in the world. The uses of machine learning become trending, and massive improvement technology has widely used in modern agricultural technology. Artificial Intelligent techniques are being used extensively in the agricultural sector as one purpose to increase the accuracy and to find solutions to the problems. As implementation of Artificial Intelligent (AI) based on Convolutional Neural Networks (CNN) application in several fields, indicates that CNN based machine learning scheme is adaptable and implemented on an agricultural area. In this contribution, we apply CNN based feature extraction on cocoa beans images. Cocoa beans images used in this study were cocoa beans (Theobroma Cacao L.) in various quality classes originating from districts in South Sulawesi, Indonesia, and we separate those images 30% for training and the remaining 70% for testing. From our assessment, the result shows that we can achieve 82.14% accuracy to classify seven classes of cocoa beans images using 5 CNN layers.
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Adhitya, Y., Prakosa, S.W., Köppen, M., Leu, JS. (2019). Convolutional Neural Network Application in Smart Farming. In: Berry, M., Yap, B., Mohamed, A., Köppen, M. (eds) Soft Computing in Data Science. SCDS 2019. Communications in Computer and Information Science, vol 1100. Springer, Singapore. https://doi.org/10.1007/978-981-15-0399-3_23
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DOI: https://doi.org/10.1007/978-981-15-0399-3_23
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