Scholarlink

The Kisan App will enable real-time in situ identification, classification of all plant and animal diseases with advance machine learning capabilities. State-of-the-art object detection using latest YOLOv9 helps yield high accuracy for efficiency, working well even at diverse data variations of multiple different diseases. Accuracy in diagnoses that farmers are accorded includes current outbreak notifications combined with real actionable preventive strategies at their disposal in the application. Effectiveness is verified by key performance metrics, such as mAP, precision, recall, and F1-score. Using an intuitive mobile application, farmers can upload images of crops or livestock for diagnosis and then receive preventive recommendations specific to identified diseases. Key functionalities include image uploads, result display, personalized notification, feedback mechanisms for users to improve accuracy, and geographic-based alerts that inform nearby regions to take action in the event of a potential outbreak.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Leveraging YOLOv9 and Deep Learning for Plant and Animal Disease Detection and Management

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Sarika Pabalkar,
  • Annaveer Mashal,
  • Tanmay Phalke,
  • Sameer Sanap,
  • Athang Patel

摘要

The Kisan App will enable real-time in situ identification, classification of all plant and animal diseases with advance machine learning capabilities. State-of-the-art object detection using latest YOLOv9 helps yield high accuracy for efficiency, working well even at diverse data variations of multiple different diseases. Accuracy in diagnoses that farmers are accorded includes current outbreak notifications combined with real actionable preventive strategies at their disposal in the application. Effectiveness is verified by key performance metrics, such as mAP, precision, recall, and F1-score. Using an intuitive mobile application, farmers can upload images of crops or livestock for diagnosis and then receive preventive recommendations specific to identified diseases. Key functionalities include image uploads, result display, personalized notification, feedback mechanisms for users to improve accuracy, and geographic-based alerts that inform nearby regions to take action in the event of a potential outbreak.