TL;DR
This work proposes an ensemble transfer learning approach that combines the advances of Inception V3 and shallow convolutional neural network models that outperforms the state-of-the-art models, offering significant value in addressing agricultural challenges.
Many leaf diseases have significant effects on yield and quality and wheat is an important crop contributing to food security globally. Accurate and timely diagnosis of these diseases is important for the sustainable use of agriculture. This study assesses the effectiveness of deep learning (DL) technique using ResNet...
Agriculture is a leading economical sector that contributes significantly to the livelihoods and the total Gross Domestic Product (GDP) of Pakistan. With cotton as a key crop, its production must be sustainable, and this becomes a challenge posed by environmental changes, pest infestations, and the increasing costs of...
India’s economy is heavily reliant on agriculture, with a diverse array of crops grown on vast tracts of land. Fruit cultivation, especially papaya, has become more popular in recent years because of its high nutritional and financial value. To increase yield, maximize resource use and lessen reliance on chemical pesti...
A comprehensive and systematic review of state-of-the-art methods for detecting potato leaf disease, covering convolutional neural networks, transformer-based architectures, and hybrid models, and a strategic comparative analysis is conducted.
The timely detection of plant health status is essential for achieving several benefits, such as increasing crop yield, reducing the use of toxic crop inputs, promoting healthier crops, and improving economic returns. A computer-aided plant status identification system enables plant health assessment using plant leaves...
Background: Legumes, such as beans, are important in worldwide agriculture because of their nutritional value and soil-enriching qualities. However, bean crops are susceptible to diseases such as angular leaf spot and rust, which may reduce production and quality. Disease identification that is both effective and timel...
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