MUMBAI, India, June 16 -- Intellectual Property India has published a patent application (202611053887 A) filed by Mr. Utkarsh Dixit; Naveen Krishna Gupta; Piyush Gola; Neeraj Kumar; and Mr. Dhyanendra Jain, Ghaziabad, Uttar Pradesh, on April 28, for 'agrivision: an image-based system for automated plant nutrient deficiency diagnosis using convolutional neural networks.'
Inventor(s) include Mr. Utkarsh Dixit; Naveen Krishna Gupta; Piyush Gola; Neeraj Kumar; and Mr. Dhyanendra Jain.
The application for the patent was published on June 5, under issue no. 23/2026.
According to the abstract released by the Intellectual Property India: "Plants respond to nutrient deficiencies in terms of health and production. Conventional diagnosis is manual and relies on expert knowledge and is labour-intensive, which is not scalable for large and precision farming. AgriVision is a new image-based plant nutrient deficiency detection system which uses computer vision, image processing and deep learning to detect common macro- and micronutrient deficiencies. The system process involves image acquisition, pre-processing, segmentation, feature extraction and classification using Convolutional Neural Networks (CNNs). It automatically recognises the predominant symptoms of chlorosis, necrosis, interveinal yellowing and distortion from the deficiencies of nitrogen, phosphorus, potassium, magnesium, sulfur and other nutrients. Our experiments demonstrate that deep learning approaches outperform rule-based approaches to detect subtle spatial and colour features with better accuracy and efficiency. Keywords: Plant nutrient deficiency, convolutional neural networks, deep learning, image classification, precision agriculture, leaf image analysis, chlorosis detection, computer vision."
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