Discrimination of sunflower seeds using multispectral and texture dataset in combination with region selection and supervised classification methods-Reference-Cited by-同舟云学术

Discrimination of sunflower seeds using multispectral and texture dataset in combination with region selection and supervised classification methods

Author:

Bantan Rashad A. R.¹^ORCID,Ali Aqib²^ORCID,Naeem Samreen²^ORCID,Jamal Farrukh³^ORCID,Elgarhy Mohammed⁴^ORCID,Chesneau Christophe⁵^ORCID

Affiliation:

1. Department of Marine Geology, Faculty of Marine Science, King Abdulaziz University, Jeddah 21551, Saudi Arabia

2. Department of Computer Science & IT, Glim Institute of Modern Studies, Bahawalpur 61300, Pakistan

3. Department of Statistics, The Islamia University of Bahawalpur, Bahawalpur, Punjab 63100, Pakistan

4. Valley High Institute for Management Finance and Information Systems, Obour, Qaliubia 11828, Egypt

5. Department of Mathematics, Université de Caen, LMNO, Campus II, Science 3, 14032 Caen, France

Funder

The Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah, Saudi Arabia

Publisher

AIP Publishing

Subject

Applied Mathematics,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics

Link

Reference27 articles.

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5. SunNet: A Deep Learning Approach to Detect Sunflower Disease;2023 7th International Conference on Trends in Electronics and Informatics (ICOEI);2023-04-11