Tomato leaf disease identification by restructured deep residual dense network

C Zhou, S Zhou, J Xing, J Song - IEEE Access, 2021 - ieeexplore.ieee.org
As COVID-19 spread worldwide, many major grain-producing countries have adopted
measures to restrict their grain exports; food security has aroused great concern from …

[HTML][HTML] A hybrid model of ghost-convolution enlightened transformer for effective diagnosis of grape leaf disease and pest

X Lu, R Yang, J Zhou, J Jiao, F Liu, Y Liu, B Su… - Journal of King Saud …, 2022 - Elsevier
Disease and pest are the main factors causing grape yield reduction. Correct and timely
identification of these symptoms are necessary for the vineyard. However, the commonly …

Grapenet: A lightweight convolutional neural network model for identification of grape leaf diseases

J Lin, X Chen, R Pan, T Cao, J Cai, Y Chen, X Peng… - Agriculture, 2022 - mdpi.com
Most convolutional neural network (CNN) models have various difficulties in identifying crop
diseases owing to morphological and physiological changes in crop tissues, and cells …

Grape leaf spot identification under limited samples by fine grained-GAN

C Zhou, Z Zhang, S Zhou, J Xing, Q Wu, J Song - Ieee Access, 2021 - ieeexplore.ieee.org
In practice, early detection of disease is of high importance to practical value, corresponding
measures can be taken at the early stage of plant disease. However, in the early stage of …

Handling severity levels of multiple co-occurring cotton plant diseases using improved YOLOX model

SK Noon, M Amjad, MA Qureshi, A Mannan - IEEE Access, 2022 - ieeexplore.ieee.org
Automatic detection of plant diseases has emerged as a challenging field in the last decade.
Computer vision-based advancements have helped in the timely and accurate identification …

A dual-track feature fusion model utilizing Group Shuffle Residual DeformNet and swin transformer for the classification of grape leaf diseases

R Karthik, GV Vardhan, S Khaitan, RNR Harisankar… - Scientific Reports, 2024 - nature.com
Grape cultivation is important globally, contributing to the agricultural economy and
providing diverse grape-based products. However, the susceptibility of grapes to disease …

Algorithms and models for automatic detection and classification of diseases and pests in agricultural crops: A systematic review

M Francisco, F Ribeiro, J Metrolho, R Dionisio - Applied Sciences, 2023 - mdpi.com
Plant diseases and pests significantly influence food production and the productivity and
economic profitability of agricultural crops. This has led to great interest in developing …

Optimized classification model for plant diseases using generative adversarial networks

S Lamba, P Saini, J Kaur, V Kukreja - Innovations in Systems and Software …, 2023 - Springer
The agricultural industry, the service sector, and the food processing industry are just a few
of the many aspects that affect a country's economy. One of the most important sectors of the …

A multi-source data fusion decision-making method for disease and pest detection of grape foliage based on ShuffleNet V2

R Yang, X Lu, J Huang, J Zhou, J Jiao, Y Liu, F Liu… - Remote Sensing, 2021 - mdpi.com
Disease and pest detection of grape foliage is essential for grape yield and quality. RGB
image (RGBI), multispectral image (MSI), and thermal infrared image (TIRI) are widely used …

Grape leaf diseases identification system using convolutional neural networks and Lora technology

Z Zinonos, S Gkelios, AF Khalifeh, DG Hadjimitsis… - IEEE …, 2021 - ieeexplore.ieee.org
Image transmission over Low-Power Wide Area Networks (LP-WAN) protocols has always
been a difficult task since it necessitates high data rates and high energy consumption. Long …