Our paper's main goal is to use an effective deep learning framework for disease prediction by making use of leaf images and to create a solution for greenhouse based on IoT to detect problems without the need for human involvement and regulating environmental parameters like humidity, temperature...
This study provides guidelines that will be useful to the research community in the context of the selection and construction of datasets. 展开 关键词: plant disease prediction classification detection dataset survey machine learning deep learning ...
had a lot of success with image classification tasks. In this study, they have demonstrated how DNNs can be used for plant disease detection in the context of image classification. Finally, this research compares existing techniques in terms of accuracy of 80%, 85%, 90%, and 95% for TL, ...
Finally, we visualized the prediction distributions of different OOD detection methods and discussed the selection of thresholds. Overall, this work lays the foundation for unknown plant disease recognition, providing strong support for the security and reliability of plant disease recognition systems. We...
A Comprehensive Review on Crop Disease Prediction Based on Machine Learning and Deep Learning Techniques Chapter © 2023 Background Plant diseases and pests detection is a very important research content in the field of machine vision. It is a technology that uses machine vision equipment to acqu...
seasonal and regional. Similarly, the characteristics of the same disease or pest at different growing stages of crops are different. Images of different plant species vary from region to region. As a result, most of the existing research results are not universal. Even with a high recognition ...
ResearchPublished on:1 February 2025 Full Text PDF Genome-wide association mapping and genomic prediction analyses reveal the genetic architecture of grain yield and agronomic traits under drought and optimum conditions in maize Drought is a major abiotic stress in sub-Saharan Africa, impacting maize ...
we are striving to implement a mobile application or web-enabled service utilizing the trained model derived from this research to support a wider plant disease research community to benefit the agricultural sector. Also, to move toward a more lightweight disease classification, model quantization, an...
Lijo, J. Analysis of Effectiveness of Augmentation in Plant Disease Prediction using Deep Learning. In Proceedings of the 2021 5th International Conference on Computing Methodologies and Communication (ICCMC), Erode, India, 8–10 April 2021; pp. 1654–1659. [Google Scholar] [CrossRef] Sun, Y....
In this paper, we present a framework for automating disease detection by the use of a tailored DL architecture. Both the Plant Village dataset and the real-time field dataset are utilized in the testing process. Our model’s results are compared to those of other spatial exploitation models....