A systematic review of deep learning techniques for plant diseases

I Pacal, I Kunduracioglu, MH Alma, M Deveci… - Artificial Intelligence …, 2024 - Springer
Agriculture is one of the most crucial sectors, meeting the fundamental food needs of
humanity. Plant diseases increase food economic and food security concerns for countries …

Transformative Role of Artificial Intelligence in Advancing Sustainable Tomato (Solanum lycopersicum) Disease Management for Global Food Security: A …

B Sundararaman, S Jagdev, N Khatri - Sustainability, 2023 - mdpi.com
The growing global population and accompanying increase in food demand has put
pressure on agriculture to produce higher yields in the face of numerous challenges …

DFN-PSAN: Multi-level deep information feature fusion extraction network for interpretable plant disease classification

G Dai, Z Tian, J Fan, CK Sunil, C Dewi - Computers and Electronics in …, 2024 - Elsevier
Accurate identification of crop diseases is an effective way to promote the development of
intelligent and modernized agricultural production, as well as to reduce the use of pesticides …

Systematic study on deep learning-based plant disease detection or classification

CK Sunil, CD Jaidhar, N Patil - Artificial Intelligence Review, 2023 - Springer
Plant diseases impact extensively on agricultural production growth. It results in a price hike
on food grains and vegetables. To reduce economic loss and to predict yield loss, early …

[HTML][HTML] Monitoring maize canopy chlorophyll content throughout the growth stages based on UAV MS and RGB feature fusion

W Li, K Pan, W Liu, W Xiao, S Ni, P Shi, X Chen, T Li - Agriculture, 2024 - mdpi.com
Chlorophyll content is an important physiological indicator reflecting the growth status of
crops. Traditional methods for obtaining crop chlorophyll content are time-consuming and …

[HTML][HTML] Integration of remote sensing and machine learning for precision agriculture: a comprehensive perspective on applications

J Wang, Y Wang, G Li, Z Qi - Agronomy, 2024 - mdpi.com
Due to current global population growth, resource shortages, and climate change, traditional
agricultural models face major challenges. Precision agriculture (PA), as a way to realize the …

Deep migration learning-based recognition of diseases and insect pests in Yunnan tea under complex environments

Z Li, J Sun, Y Shen, Y Yang, X Wang, X Wang, P Tian… - Plant Methods, 2024 - Springer
Background The occurrence, development, and outbreak of tea diseases and pests pose a
significant challenge to the quality and yield of tea, necessitating prompt identification and …

Global wavelet-integrated residual frequency attention regularized network for hypersonic flight vehicle fault diagnosis with imbalanced data

Y Dong, H Jiang, Y Liu, Z Yi - Engineering Applications of Artificial …, 2024 - Elsevier
In the context of long-term exposure to harsh operating conditions, the hypersonic flight
vehicle (HFV) is susceptible to failure. Regrettably, the current fault diagnosis methods for …

[HTML][HTML] Advancing plant disease classification: A robust and generalized approach with transformer-fused convolution and Wasserstein domain adaptation

MH Tunio, J ping Li, X Zeng, A Ahmed, SA Shah… - … and Electronics in …, 2024 - Elsevier
Plant diseases pose significant threats to agricultural productivity and food security. Owing to
a scarcity of field environment datasets, the prevailing plant disease classification …

UPFormer: U-sharped perception lightweight transformer for segmentation of field grape leaf diseases

X Zhang, F Li, H Zheng, W Mu - Expert Systems with Applications, 2024 - Elsevier
In the smart agriculture community, segmentation models are de-facto for the timely
detection and identification of plant diseases. However, the complex background and the …