A Review of Image-Based Detection Techniques

Authors

  • Felcy Judith Department of Computer Science and Engineering, KVIT Raipur, Chhattisgarh, India
  • Mohammed Shahid Sultan Assistant Professor, Department of Computer Science and Engineering, KVIT Raipur, Chhattisgarh, India

DOI:

https://doi.org/10.66069/ojspub.16560802

Keywords:

Machine Learning (ML), Convolutional Neural Network (CNN) [1], Artificial Intelligence (AI), Image Processing

Abstract

Plant leaf disease detection is a crucial aspect of precision agriculture and crop management, helping to prevent crop losses and improves yield quality. Plants are very essential in our life they provide source of energy and overcome the matter of global warming. Plant disease is notable risk of nutrition security. Therefore, timely detection of risk is important. Leaf disease detection using the machine learning is an approach. Machine learning offers a worthy approach for making a classy and automatic algorithm using Convolutional Neural Network (CNN), Artificial Intelligence (AI), Image Processing and video processing, voice processing, Natural Language Processing, etc. This review report provides the comparative analysis of the different machine learning algorithms of diagnosis of different leaf disease.

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Published

2026-08-30

How to Cite

Judith, F., & Sultan, M. S. (2026). A Review of Image-Based Detection Techniques. Journal of Research in Science and Engineering, 8(8), 5–6. https://doi.org/10.66069/ojspub.16560802

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Section

Articles

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