Xing S, Lee M, Lee K-K (2019) Citrus pests and diseases recognition model using weakly dense connected convolution network. Sensors 19(14):3195 Article Google Scholar D. S. Joseph, P. M. Pawar, and K. Chakradeo, “Real-time plant disease dataset development and detection of plant dise...
The detection and classification of crop diseases is an essential use of DL, ML, and computer vision techniques in agriculture industries [1]. The aim is to develop algorithms and techniques based on images of leaves or other plant features that can automatically detect and classify agricultural p...
Panchal AV, Patel SC, Bagyalakshmi K et al (2023) Image-based plant diseases detection using deep learning. MMater Today 80:3500–3506. https://doi.org/10.1016/j.matpr.2021.07.281,sI:5 NANO 2021 Panigrahi KP, Das H, Sahoo AK et al (2020) Maize leaf disease detection and classificati...
Plant diseases pose significant threats to agriculture, impacting both food safety and public health. Traditional plant disease detection systems are typically limited to recognizing disease categories included in the training dataset, rendering them ine
abundant use of chemicals such as bactericides, fungicides, and nematicides to control plant diseases has been causing adverse effects in the agro-ecosystem. Currently, there is a need for effective early disease detection techniques to control plant diseases for food security and sustainability of ...
Notably, how plant pests and diseases can be appropriately detected and timely prevented is a hotspot paradigm in smart, sustainable agriculture remains unknown. In recent years, deep transfer learning has demonstrated tremendous advances in the recognition accuracy of object detection and image ...
RQ2: How do different models perform in the classification, detection, and segmentation of plant diseases? RQ3: What are the popular computer vision methods used in deep learning models for plant diseases? RQ4: What are the commonly preferred datasets in deep learning models for plant diseases?
The use of machine learning and learning techniques to identify plant leaf categories and diagnose diseases has brought a wave of advancement in agriculture. This study focuses on the use of regression (LR) to identify and classify plant leaf diseases. Kaggle's diverse datasets, covering a range...
how plant pests and diseases can be appropriately detected and timely prevented is a hotspot paradigm in smart, sustainable agriculture remains unknown. In recent years, deep transfer learning has demonstrated tremendous advances in the recognition accuracy of object detection and image classification syste...
Trends and prospect of machine vision technology for stresses and diseases detection in precision agriculture. AgriEngineering. 2023;5(1):20–39. 3. Shamsul Kamar NA, Abd Rahim SK, Ambrose AA, Awing NH, Samdin Z, Hassan A, Saleh MN, Terhem R. Pest and disease incidence of coniferous ...