MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202621052282 A) filed by Gopal Deshmukh; Abhishek Kadam; Rohan Kadam; Sakshi Jannawar; and Atharv Jadhav on April 24, 2026, for Appleguard: An Intelligent Deep Learning-Based System For Apple Disease Detection And Stage Prediction.
Inventors include Gopal Deshmukh; Abhishek Kadam; Rohan Kadam; Sakshi Jannawar; and Atharv Jadhav.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: AppleGuard is an intelligent machine learning-based system designed to detect apple diseases and predict their s image processing and deep learning techniques. The system utilizes a Convolutional Neural Network automatically extract important visual features such as color variation, texture patterns, and lesion characteristics images of apples. A labeled dataset consisting of healthy and diseased apple samples is used to train the model accurate classification of diseases such as apple scab, black rot, and cedar apple rust. To improve model performance and generalization, preprocessing techniques like image resizing, normalization augmentation (rotation, flipping, and brightness adjustment) are applied. In addition to disease identification, t also performs stage detection by categorizing the severity of infection into early, intermediate, and advanced le helps in understanding the progression of the disease and supports timely intervention. The trained model is integrated into a user-friendly interface where users can upload apple images and receive predictions. The system provides fast, reliable, and automated results, reducing dependency on manual inspection knowledge. AppleGuard aims to assist farmers and agricultural stakeholders in early disease detection, impro quality, reducing losses, and promoting precision agriculture practices. The system is scalable and can be extende crops and plant diseases, making it a versatile solution for smart farming applications.
Disclaimer: Curated by HT Syndication.
