RiceNet: A deep convolutional neural network approach for classification of rice varieties

Author:

Din Nusrat Mohi UdORCID,Assad Assif,Dar Rayees AhmadORCID,Rasool Muzafar,Sabha Saqib Ul,Majeed Tabasum,Islam Zahir UlORCID,Gulzar Wahid,Yaseen Aamir

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference49 articles.

1. Rice grain disease identification using dual phase convolutional neural network based system aimed at small dataset.;Ahmed;agriRxiv,2021

2. Classification of watermelon seeds using morphological patterns of X-ray imaging: A comparison of conventional machine learning and deep learning;Ahmed;Sensors,2020

3. Identification of haploid and diploid maize seeds using convolutional neural networks and a transfer learning approach;Altuntaş;Computers and Electronics in Agriculture,2019

4. Inspection of paddy seed varietal purity using machine vision and multivariate analysis;Ansari;Journal of Agriculture and Food Research,2021

5. Nutritional profiling of pigmented and scented rice genotypes of kashmir himalayas;Ashraf;Journal of Pharmacognosy and Phytochemistry,2017

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