yolov7 Computer Vision Project
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Here are a few use cases for this project:
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Agricultural Health Monitoring: yolov7 can help agriculturists and crop growers to identify diseases like bacterial blight and curl virus in real-time. This will make it easier to take prompt action, thus reducing the chances of disease spread and crop loss.
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Smart Gardening: This computer vision model can be used in home gardening applications or systems to identify signs of these specific infections. Based on the yolov7 results, the system could provide recommendations for treatment or care.
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Educational Research: Biology and agriculture students can use yolov7 to study the appearance and spread of bacterial blight and curl virus on various types of plants, aiding in their comprehension and learning about plant diseases.
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Plant Conservation: Conservationists can use this model to monitor valued or endangered plants and take action if a disease is identified, preserving biodiversity and important species.
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Drone Crop Surveillance: Drones equipped with cameras and yolov7 can be used for large scale farms. The aerial data collected can help in identifying unhealthy plants, enabling precise and efficient care.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
yolov7-dbsvc_dataset,
title = { yolov7 Dataset },
type = { Open Source Dataset },
author = { rahim kolachi },
howpublished = { \url{ https://universe.roboflow.com/rahim-kolachi-czmtb/yolov7-dbsvc } },
url = { https://universe.roboflow.com/rahim-kolachi-czmtb/yolov7-dbsvc },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { dec },
note = { visited on 2024-12-22 },
}