The proposed Sugarcane Leaf Disease Detection and Classification System provides a fast, accurate, and user-friendly solution for automated disease diagnosis and contributes to improved crop management, reduced crop losses, and enhanced agricultural productivity.
The proposed automated leaf disease detection system using image processing and deep learning techniques can detect leaf diseases effectively and efficiently, making it a useful and cost-effective solution for supporting farmers and agricultural experts in early disease diagnosis.
Shilpa T. S., K. U, Anusha Jajur J· World Journal of Advanced En...· 0 citations
Plant leaf diseases significantly reduce agricultural productivity and crop yield worldwide, making early and accurate detection essential to prevent large-scale crop damage. Traditional disease identification methods rely on manual inspection by experts, which is time-consuming, costly, and often inaccessible to farme...
Kuppala Ajay Kumar, Yella Sai Krishna, R. Kumar et al.· 2026 6th International Confe...· 0 citations
Agriculture is a key component in ensuring food security in the world and one of the most common staple foods in the world is rice. But there are a number of leaf diseases affecting rice, like bacterial leaf blight, brown spot, and rice blast, which cause lower production yield. In order to limit economic losses, it is...
Vandana Samanthula, N. Valli, Sultanov Sirojiddin et al.· 2026 6th International Confe...· 0 citations
Plant diseases are among the most significant challenges in agriculture because they reduce crop productivity and cause economic losses to farmers. Early monitoring of plant diseases is important for controlling infection spread and improving crop management. Traditional plant disease detection techniques depend heavil...
Radha Krishna Mukkapati, Jayendra Nelakurthi, P. R. et al.· International Conference Com...· 0 citations
The Plant Disease Detecting System leverages advances in artificial intelligence and deep learning to provide an automated, efficient, and reliable solution for identifying plant diseases at an early stage and contributes to increased crop productivity, reduced chemical usage, and sustainable farming practices.
Plant leaf diseases are known to affect agricultural productivity and food security on a global level. "Therefore, the detection and diagnosis of diseases are important aspects of maintaining the health of crops on a sustainable level. Traditionally, the detection of diseases in plants is performed manually by experts....
