Trends in vision-based machine learning techniques for plant disease identification: A systematic review
Globally, all the major crops are significantly affected by diseases every year, as manual
inspection across diverse fields is time-consuming, tedious, and requires expert knowledge …
inspection across diverse fields is time-consuming, tedious, and requires expert knowledge …
Deep neural networks to detect weeds from crops in agricultural environments in real-time: A review
Automation, including machine learning technologies, are becoming increasingly crucial in
agriculture to increase productivity. Machine vision is one of the most popular parts of …
agriculture to increase productivity. Machine vision is one of the most popular parts of …
Corn leaf diseases diagnosis based on K-means clustering and deep learning
H Yu, J Liu, C Chen, AA Heidari, Q Zhang… - IEEE …, 2021 - ieeexplore.ieee.org
Accurate diagnosis of corn crop diseases is a complex challenge faced by farmers during
the growth and production stages of corn. In order to address this problem, this paper …
the growth and production stages of corn. In order to address this problem, this paper …
A systematic literature review on plant disease detection: Motivations, classification techniques, datasets, challenges, and future trends
Plant pests and diseases are a significant threat to almost all major types of plants and
global food security. Traditional inspection across different plant fields is time-consuming …
global food security. Traditional inspection across different plant fields is time-consuming …
Learning multiple attention transformer super-resolution method for grape disease recognition
H Jin, X Chu, J Qi, J Feng, W Mu - Expert Systems with Applications, 2024 - Elsevier
Grape leaf disease is a primary factor affecting grape yield and impeding the growth of the
industrial economy. Currently, high-quality datasets are required for deep recognition …
industrial economy. Currently, high-quality datasets are required for deep recognition …
LightMixer: A novel lightweight convolutional neural network for tomato disease detection
Y Zhong, Z Teng, M Tong - Frontiers in Plant Science, 2023 - frontiersin.org
Tomatoes are among the very important crops grown worldwide. However, tomato diseases
can harm the health of tomato plants during growth and reduce tomato yields over large …
can harm the health of tomato plants during growth and reduce tomato yields over large …
An improved deep residual convolutional neural network for plant leaf disease detection
In this research, we proposed a novel deep residual convolutional neural network with 197
layers (ResNet197) for the detection of various plant leaf diseases. Six blocks of layers were …
layers (ResNet197) for the detection of various plant leaf diseases. Six blocks of layers were …
[HTML][HTML] Weedgan: a novel generative adversarial network for cotton weed identification
Recently, precision weed management has emerged as a promising solution for reducing
the use of herbicides which is hazardous to crops and human health. Thus, accurate …
the use of herbicides which is hazardous to crops and human health. Thus, accurate …
[PDF][PDF] RDA-CNN: Enhanced Super Resolution Method for Rice Plant Disease Classification.
K Sathya, M Rajalakshmi - Computer Systems Science & …, 2022 - cdn.techscience.cn
In the field of agriculture, the development of an early warning diagnostic system is essential
for timely detection and accurate diagnosis of diseases in rice plants. This research focuses …
for timely detection and accurate diagnosis of diseases in rice plants. This research focuses …
[HTML][HTML] On the application of image augmentation for plant disease detection: A systematic literature review
Agriculture significantly influences the global economy, especially in developing countries,
but plant diseases can drastically reduce crop yields and economic gains if not detected …
but plant diseases can drastically reduce crop yields and economic gains if not detected …