Enhancing LSD Image Classification Techniques A Literature Review on Classification Techniques
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 ApproachesPublished
Issue
Section
License
Copyright (c) 2024 International Journal on Emerging Research Areas

This work is licensed under a Creative Commons Attribution 4.0 International License.
All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
How to Cite
Similar Articles
- Alen Siju Mudakodil, Alwin J Thomas, Awindas R, Chris Reji Kuriakose, Sarju S, NeuroRoad: An AI-Assisted Role-Based Learning Management System for Neurodivergent Education , International Journal on Emerging Research Areas: Vol. 6 No. 1 (2026): IJERA
- Athulya Anilkumar, Abhinav V V, Aneeta Shajan, Anjana S Nair, Bini M Issac, R Neenu, Image Descriptor For Visually Impaired , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Ria Mathews, AI Based Stress and Mental Health Monitoring System Using Chatbot, Speech and Facial Analysis , International Journal on Emerging Research Areas: Vol. 6 No. 1 (2026): IJERA
- Tom Kurian, Ektha P S, Chethana Raj T, Diona Joseph, Annu Mary Abraham, Intelligent Disease Prediction in Hydroponic Systems Using Machine Learning , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Rehan T Raj, Rinil Johns, Reema Maria Suresh, Reema Maria Suresh, Nehala Noushad, Anishamol Abraham, A Survey of Automatic Brain Tumor Detection and Classification Techniques , International Journal on Emerging Research Areas: Vol. 6 No. 2 (2026): IJERA
- Shiney Thomas, Elsa George, Alphonsa Francis, Anna Job, Ann Maria James, Wildlife Detection And Recognition Using YOLO V8 , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
- Akhil Shaji, Albin Joshy, M J Athulkrishna, Joel Biju, Bino Thomas, COLLEGE BUS SECURITY AND MANAGEMENT SYSTEM , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Nehala Noushad, Nikhitha Thomas, Reema Maria Suresh, Rehan T Raj , Resmipriya M G, AI-Based Analysis of Road Congestion Causes Using Real-Time Traffic Camera Data , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Sebastian Biju, Samuel Michael, Thomas Mathew Jose, Mathew Abraham, Minu Cherian, A Review of Machine Learning Approaches for Canine Skin Disease Detection Using Image Processing Techniques , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
- Joel Jones, Jaick T Kurian, Jesvin Jelson Thachil, Drishya K. V., Aswin Nandakumar, A Comprehensive Review of Graph-Based Forensic Timeline Reconstruction: Analysis of the Timelance Framework , International Journal on Emerging Research Areas: Vol. 6 No. 1 (2026): IJERA
You may also start an advanced similarity search for this article.
