Advancements in Communication and Systems
Comparative Analysis of Deep Learning Techniques for Automated Plant Leaf Disease Detection: A Comprehensive Survey
Authors: Deepraj Evane, Meenu Chawla and Namita Tiwari
Publishing Date: 13-09-2024
ISBN: 978-81-955020-7-3
Abstract
Plant leaf disease detection in the early stages is very important for farmers to produce a better quantity and quality crop. Performing this task manually is very challenging and requires expertise in pathogens to detect them as early as possible and cure them with the right treatment. Automation in this industry is crucial in order to reduce manpower and treat plants at the ideal moment to avoid low recognition efficiency and poor dependability due to errors made by humans. There is extensive research happening to automize plant leaf disease detection and has received high accuracy on deep learning models to automate. The performance of various architectures such as VGG19, EfficientNet, MobileNet, and DenseNet used as across different datasets. Our analysis reveals that EfficientNet outperforms other models in terms of accuracy and MobileNet in terms of computational efficiency, making it suitable for deployment on both high-end and low-end devices. Still, there are many challenges to solve in this automation, like the cost of a high definition camera to capture plant leaf images and the computational cost to process the images. This paper concludes by discussing the challenges and opportunities for further research. The difficulties include developing more robust and precise image capture and pre-processing techniques, extracting more discriminative features, and creating more efficient and effective classification algorithms. Deep learning techniques, the development of mobile and web-based applications, and the integration of plant leaf disease detection with other agricultural technologies are all possibilities.
Keywords
Precision Agriculture, Machine Learning, Deep Learning, Computer Vision, Disease Identification, IoT (Internet of Things) in Agriculture, Sustainable Agriculture, Disease Monitoring.
Cite as
Deepraj Evane, Meenu Chawla and Namita Tiwari, "Comparative Analysis of Deep Learning Techniques for Automated Plant Leaf Disease Detection: A Comprehensive Survey", In: Ashish Kumar Tripathi and Vivek Shrivastava (eds), Advancements in Communication and Systems, SCRS, India, 2024, pp. 611-625. https://doi.org/10.56155/978-81-955020-7-3-54