会议论文详细信息
International Conference on Information Technology and Digital Applications 2018
Classifying soil texture images using transfer learning
计算机科学;无线电电子学
Guidang, E.P.B.^1
Abra State Institute of Sciences and Technology, Lagangilang, Abra, Philippines^1
关键词: Feature mining;    Literature reviews;    Machine learning techniques;    Soil textures;    Trained neural networks;    Transfer learning;    Transfer learning methods;   
Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/482/1/012042/pdf
DOI  :  10.1088/1757-899X/482/1/012042
学科分类:计算机科学(综合)
来源: IOP
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【 摘 要 】

Transfer learning is a machine learning technique which makes use of a pre-trained neural network to classify new objects. This study was conducted to evaluate the performance of Inception-v3 in classifying Soil texture images on different conditions. Specifically it achieved the following objectives 1) Identified the features of Inception-v3 and 2) Classified Soil Texture images using Inception-v3. The study used literature review to identify the features of Inception-v3. The study found that Transfer Learning comprises of two portions: a) feature mining and b) classification. Moreover, Inception-v3 highest prediction rating of a Soil texture image is 98% and 86% as the lowest. The study concludes that Transfer Learning method through the use of Inception-v3 can be used to classify Soil texture images.

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