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Deep learning based classification for paddy pests & diseases recognition

Published:20 April 2018Publication History

ABSTRACT

Pests and diseases are a threat to paddy production, especially in Indonesia, but identification remains to be a challenge in massive scale and automatically. Increasing smartphone usage and deep learning advance create an opportunity to answer this problem. Collecting 4,511 images from four language using search engines, and augment it to develop diverse data set. This dataset fed into CaffeNet model and processed with Caffe framework. Experiment result in the model achieved accuracy 87%, which is higher than random selection 7.6%.

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      cover image ACM Other conferences
      ICMAI '18: Proceedings of 2018 International Conference on Mathematics and Artificial Intelligence
      April 2018
      95 pages
      ISBN:9781450364201
      DOI:10.1145/3208788

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      Publication History

      • Published: 20 April 2018

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