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@article{180198,
        author = {Kalariya Ankitkumar Keshavlal and Yagnesh Shukla},
        title = {Comparative Study of Deep Learning Object Detection Methods for Wheat Leaf Disease Detection with Organic Remedy Suggestions - A Review},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {274-278},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180198},
        abstract = {The wheat leaf diseases pose a significant 
threat to global agricultural productivity, necessitating 
the development of efficient and accurate detection 
techniques. Recently, development in deep learning 
(DL) algorithms have completely given new outlook 
how plant diseases can be detected with the use of 
object detection models. This review compares leading 
deep learning (DL) based object detection techniques 
like 
Single-Shot 
Multi-Box 
Detector 
(SSD), 
Convolutional Neural Networks (CNN), Faster R
CNN, YOLO version 5 (You Look Only Once), and 
YOLO version 8 for identifying diseases in wheat leaf. 
It exhibits comparative study of each model’s mean 
average precision, architecture, and its speed. 
Additionally, the review also shows that the likely hood 
of using organic remedies as a natural and sustainable 
way to manage plant diseases. While old and 
traditional chemical treatments are helpful but they 
lead to environmental impact. As an alternative, 
organic remedies like biopesticides, neem extracts, and 
microbial formulations can be effective. The study 
shows evaluation of the strengths and weaknesses 
among various detection models in terms of mean 
average precision, computational cost and real-life 
disease monitoring. 
Findings show that YOLOv8 offers both high speed 
and accuracy, while Faster R-CNN is particularly 
strong in accuracy. SSD and CNN provide a balanced 
performance, 
making 
them 
well-suited 
for 
environments with limited resources. By integrating 
deep learning with organic disease control methods, 
this review promotes a sustainable action to protect 
wheat crops.},
        keywords = {Convolutional Neural Networks (CNN),  Faster Region Based CNN (Faster R-CNN), Single Shot Multi-Box Detector (SSD), You Look Only Once  (YOLOv5), You Look Only Once (YOLOv8)},
        month = {May},
        }