Advanced Computational Techniques for Plant Disease Detection
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Agricultural Science and Technology".
Deadline for manuscript submissions: 20 December 2024 | Viewed by 742
Special Issue Editors
Interests: deep learning; computer vision; large scale image classification; plant identification
Special Issues, Collections and Topics in MDPI journals
Interests: visual computing; image search; image recognition
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the realm of agriculture, the timely detection of plant diseases is crucial for ensuring crop health and productivity. With the advent of digital technology, advanced computational techniques have emerged as powerful tools in this endeavor. These techniques leverage cutting-edge algorithms and machine learning models that can be used to analyze vast amounts of data, from high-resolution images to environmental sensors, as well as identify patterns and anomalies indicative of disease. The integration of these advanced computational techniques with traditional agricultural practices has led to smarter, more efficient, and sustainable farming practices. As research continues to advance, the potential for the early detection, prevention, and management of plant diseases will only grow, ultimately benefiting global food supply and the environment.
Dr. Haixi Zhang
Dr. Zhaoqiang Xia
Guest Editors
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Keywords
- plant disease detection
- machine learning
- computer vision
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