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Enhancing LSD Image Classification Techniques A Literature Review on Classification Techniques

Authors

  • Dr.Sinciya P.O

    Amal Jyothi College of Engineering
    Author
  • Ameena Ismail

    Amal Jyothi College of Engineering
    Author
  • Christin Abu

    Amal Jyothi College of Engineering
    Author
  • Don P Mathew

    Amal Jyothi College of Engineering
    Author
  • Gokul Krishnan G

    Amal Jyothi College of Engineering
    Author

Abstract

With an emphasis on lumpy skin disease (LSD) in cattle and other skin conditions, this paper provides an extensive literature review on current developments in disease detection approaches for livestock. Through the use of ensemble models, hybrid systems, preprocessing approaches, feature ex- traction strategies, and Convolutional Neural Networks (CNNs), researchers have significantly increased the efficiency and accu- racy of diagnostic procedures. The review summarizes the results of several studies, stressing the advantages and disadvantages of various strategies and offering information on how well they work in agricultural contexts. Integration of domain expertise with im- age analysis, employing ensemble models to improve robustness, and investigating pretreatment methods for data improvement are some of the important subjects covered. This research adds to the ongoing efforts to protect animal welfare and agricultural productivity while revolutionizing disease detection procedures by analyzing the most recent advancements in livestock health monitoring.

Keywords:

Hybrid Systems, Preprocessing Approaches
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Published

06-08-2025

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Section

Articles

How to Cite

[1]
S. P.O, A. Ismail, C. Abu, D. Mathew, and G. Krishnan G, “Enhancing LSD Image Classification Techniques A Literature Review on Classification Techniques ”, IJERA, vol. 4, no. 1, pp. 1–4, Aug. 2025, Accessed: Aug. 12, 2025. [Online]. Available: https://ijera.in/index.php/IJERA/article/view/180

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