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- W3127773147 abstract "Indonesia is an agricultural country, which has various types of plants. Starting from food plants, crops, and fruits. Some areas have different types of plants, according to the suitability of the soil and weather in the local environment. So there are some plants that sometimes people do not understand the names or types of these plants. Because in the occupied area there are no such types of plants. For example, sometimes people do not understand the types of tubers that exist in Indonesia. From these conditions, a system is made so that it can classify tuber types based on the image of the tuber with the Deep Learning algorithm. Where the tuber image data is classified into 3 types, namely sweet potatoes, cassava, and tales, each consisting of 60 images and a total of 180 images. Image data is divided into 150 image datasets and 30 test data images. Furthermore, the 150 image dataset is classified with the Deep Learning algorithm with 2 layer models, 15 layers, and 12 layers. All dataset images and test data have a size of 100x150. With 2 different layer models and test data obtained accuracy results are obtained respectively, namely: 97% and 93%." @default.
- W3127773147 created "2021-02-15" @default.
- W3127773147 creator A5056963594 @default.
- W3127773147 date "2020-11-19" @default.
- W3127773147 modified "2023-10-14" @default.
- W3127773147 title "Tuber Type Classification Based on Image of Bulbs with Deep Learning" @default.
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- W3127773147 doi "https://doi.org/10.1109/iciss50791.2020.9307584" @default.
- W3127773147 hasPublicationYear "2020" @default.
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