Abstract: Plant diseases seriously affect worldwide crop output, threatening food security and agricultural sustainability. This study solves these issues by introducing a hybrid machine learning ...
Abstract: Agriculture plays an importance role in feeding the global population; thus, timely and accurate plant diseases diagnosis is crucial to yield protection. This research implements a hybrid ...
Abstract: Detecting crop diseases is critical but labor-intensive task in agriculture, often requiring expert knowledge and manual inspection. This paper describes an efficient technique for automated ...
Abstract: Leaf diseases pose a major threat to the productivity and quality of commercial crops in the coastal and Malnad regions, renowned for their diverse and high-value agricultural practices. In ...
Abstract: Plant diseases are a serious threat to agricultural productivity and food safety at global level. This paper employs deep learning techniques to present a smart solution for automatic ...
Abstract: This paper presents a robust and efficient deep learning-based approach for plant species disease identification using images captured in realistic, natural field conditions. With the rising ...
Abstract: Fast and accurate plant disease detection is essential for agricultural production and ecologically sustainable farming. The research paper defines GACN, a Geospatial data and AI-powered ...
Abstract: In this work designs and implements an intelligent AI-powered plant disease detection and classification system through Convolutional Neural Network. This study builds on a key limitation in ...
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