Deep learning in wheat diseases classification: A systematic review

D Kumar, V Kukreja - Multimedia Tools and Applications, 2022 - Springer
The main goal of this paper is to review systematically the recent studies that have been
published and discussed WD prediction models. The literature analysis is performed based …

Applications of the remote sensing technology to detect and monitor the rust disease in the wheat–a literature review

M Khosrokhani, AH Nasr - Geocarto International, 2022 - Taylor & Francis
The wheat production loss induced by rust pathogens is huge per annum globally. Those
pathogens cause substantial fungal diseases of the wheat. Therefore, it is significant to be …

Automatic classification of wheat rust diseases using deep convolutional neural networks

V Kukreja, D Kumar - 2021 9th International Conference on …, 2021 - ieeexplore.ieee.org
Wheat is the staple food for Indians and it is one of the most common grain crops all over the
world. The wheat diseases cause a huge amount of yield losses. The wheat yield losses are …

CNN–SVM hybrid model for varietal classification of wheat based on bulk samples

MF Unlersen, ME Sonmez, MF Aslan, B Demir… - … Food Research and …, 2022 - Springer
Determining the variety of wheat is important to know the physical and chemical properties
which may be useful in grain processing. It also affects the price of wheat in the food …

Distinguishing seedling volunteer corn from soybean through greenhouse color, color-infrared, and fused images using machine and deep learning

P Flores, Z Zhang, C Igathinathane, M Jithin… - Industrial Crops and …, 2021 - Elsevier
Volunteer corn (VC; Zea mays L.), as a weed in corn-soybean (Glycine max (L.) Merr.)
rotation, has negatively impacted soybean production by reducing yield, lowering grain …

Palm tree disease detection and classification using residual network and transfer learning of inception ResNet

M Ahmed, A Ahmed - Plos one, 2023 - journals.plos.org
Agriculture has become an essential field of study and is considered a challenge for many
researchers in computer vision specialization. The early detection and classification of plant …

Enhancing wheat disease diagnosis in a greenhouse using image deep features and parallel feature fusion

Z Zhang, P Flores, A Friskop, Z Liu… - Frontiers in Plant …, 2022 - frontiersin.org
Since the assessment of wheat diseases (eg, leaf rust and tan spot) via visual observation is
subjective and inefficient, this study focused on develo** an automatic, objective, and …

[HTML][HTML] Integrated digital image processing techniques and deep learning approaches for wheat stripe rust disease detection and grading

R Mumtaz, MH Maqsood, I ul Haq, U Shafi… - Decision Analytics …, 2023 - Elsevier
This study proposes integrated image processing and deep learning approaches for wheat
rust disease detection and grading. Wheat stripe rust is one of the diseases affecting the …

Image segmentation, classification, and recognition methods for wheat diseases: Two Decades' systematic literature review

D Kumar, V Kukreja - Computers and Electronics in Agriculture, 2024 - Elsevier
Context Due to wheat diseases (WD), the global rate of wheat production is decreasing by
3.6% annually. With the help of computer vision technology, WD recognition is not a …

A Brief Overview of Deep Learning based Techniques for the Detection of Wheat Leaf Disease: A Recent Study

PP Neog, S Batra, S Saraswat… - … and Control Systems …, 2023 - ieeexplore.ieee.org
Wheat is an important cereal crop and is the second most consumed cereal after rice
globally. It is a staple food for more than one-third of the world's population. The production …