Varietal Identification of Rice Seed Using Deep Convolutional Neural Network

Authors

  • Amrit Poudel Department of Software Engineering, Gandaki College of Engineering and Science, Pokhara University, Nepal
  • Bidur Devkota Department of Electronics and Computer Engineering, IOE, Pashchimanchal Campus, Tribhuvan University, Nepal

Keywords:

CNN-SVM, Hybrid Model, Rice Dataset, Rice Seed Classification

Abstract

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Published

2022-12-31

How to Cite

Varietal Identification of Rice Seed Using Deep Convolutional Neural Network. (2022). Journal of Engineering and Sciences, 1(1), 57-61. https://doi.org/10.3126/jes2.v1i1.58428

Issue

Vol. 1 No. 1 (2022)

Section

Articles

License

Copyright (c) 2022 Amrit Poudel, Bidur Devkota

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

CC BY: This license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.

How to Cite

Varietal Identification of Rice Seed Using Deep Convolutional Neural Network. (2022). Journal of Engineering and Sciences, 1(1), 57-61. https://doi.org/10.3126/jes2.v1i1.58428