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Rice Leaves Disease Diagnose Empowered with Transfer Learning

  • Published:2022 Issue:3 Volume:42 Page:1001-1014
  • ISSN:0267-6192
  • Container-title:Computer Systems Science and Engineering
  • language:en
  • Short-container-title:

Author:

Sabri Elmitwally Nouh,Tariq Maria,Adnan Khan Muhammad,Ahmad Munir,Abbas Sagheer,Mazaed Alotaibi Fahad

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

General Computer Science,Theoretical Computer Science,Control and Systems Engineering

Reference36 articles.

1. Classification of rice leaf diseases based on morphological changes;Phadikar;Information and Electronics Engineering,2012

2. Automated rice leaf disease detection using color image analysis;Pugoy,2011

3. Grading method of leaf spot disease based on image processing;Weizheng,2008

4. A framework for detection and classification of plant leaf and stem diseases;Bashish,2010

5. Image processing techniques for diagnosing rice plant disease: A survey;Sethy;Procedia Computer Science,2020

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1. A systematic review of deep learning techniques for rice disease recognition: Current trends and future directions;Franklin Open;2024-09

2. Identification and Detection of Rice Plant Diseases by Using Neural Network;Lecture Notes in Networks and Systems;2024

3. GIS-based Meteorological Disaster Risk Assessment for Rice in Northeast China in the Context of Big Data;2023 International Conference on Computer Simulation and Modeling, Information Security (CSMIS);2023-11-15

4. Philippine Rice Disease Classification Using Deep Learning;2023 International Conference on Decision Aid Sciences and Applications (DASA);2023-09-16

5. Rice plant disease diagnosing using machine learning techniques: a comprehensive review;SN Applied Sciences;2022-10-20
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