Durum Wheat Classification Using Feature Selection, Bayesian Optimization and Support Vector-Reference-Cited by-同舟云学术

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Durum Wheat Classification Using Feature Selection, Bayesian Optimization and Support Vector

Published:2024-01-11 Issue: Volume: Page:1-6
ISSN:
Container-title:2024 Fourth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)
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Author:

Naik Nabin Kumar¹,Sethy Prabira Kumar²,Devi Appari Geetha³,Amat Rajat¹,Behera Santi Kumari⁴,Biswas Preesat⁵

Affiliation:

1. Sambalpur University,Dept. of Electronics,Odisha,India,768019

2. Guru Ghasidas Vishwavidyalaya,Department of ECE,Bilaspur,C.G.

3. P. V. P Siddhartha Institute of Technology,Dept. of ECE,Vijaywada,AP,India,520007

4. VSSUT, Burla,Dept. of CSE,Odisha,India,768018

5. GEC Jagdalpur,Department of ET&T,CG,India,494001

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10468568/10468675/10468887.pdf?arnumber=10468887

Reference20 articles.

1. DETERMINING WHEAT VITREOUSNESS USING IMAGE PROCESSING AND A NEURAL NETWORK

2. Identification of durum wheat grains by using hybrid convolution neural network and deep features

3. Detection and enumeration of wheat grains based on a deep learning method under various scenarios and scales

4. Wheat grain classification by using dense SIFT features with SVM classifier

5. Comparative analysis of Indian wheat seed classification

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