Convolutional neural networks in detection of plant leaf diseases: A review

B Tugrul, E Elfatimi, R Eryigit - Agriculture, 2022 - mdpi.com
Rapid improvements in deep learning (DL) techniques have made it possible to detect and
recognize objects from images. DL approaches have recently entered various agricultural …

[HTML][HTML] The application of deep learning in the whole potato production Chain: A Comprehensive review

RF Wang, WH Su - Agriculture, 2024 - mdpi.com
The potato is a key crop in addressing global hunger, and deep learning is at the core of
smart agriculture. Applying deep learning (eg, YOLO series, ResNet, CNN, LSTM, etc.) in …

Artificial driving based EfficientNet for automatic plant leaf disease classification

JG Kotwal, R Kashyap, PM Shafi - Multimedia Tools and Applications, 2024 - Springer
Plant disease (PD) detection is a substantial problem that needs to be tackled to develop the
economy and improve agricultural production. Using conventional methods to classify plant …

Inception convolutional vision transformers for plant disease identification

S Yu, L **e, Q Huang - Internet of Things, 2023 - Elsevier
Plant disease has a considerable influence on the safety of grain output and quality.
Therefore, it is crucial to detect and diagnose plant diseases. Most plant diseases are …

A deep features extraction model based on the transfer learning model and vision transformer “tlmvit” for plant disease classification

A Tabbakh, SS Barpanda - IEEE Access, 2023 - ieeexplore.ieee.org
This paper proposes a novel approach for extracting deep features and classifying diseased
plant leaves. The agriculture industry is negatively impacted by plant diseases causing crop …

PND-Net: plant nutrition deficiency and disease classification using graph convolutional network

A Bera, D Bhattacharjee, O Krejcar - Scientific Reports, 2024 - nature.com
Crop yield production could be enhanced for agricultural growth if various plant nutrition
deficiencies, and diseases are identified and detected at early stages. Hence, continuous …

Vision transformer meets convolutional neural network for plant disease classification

PS Thakur, S Chaturvedi, P Khanna, T Sheorey… - Ecological …, 2023 - Elsevier
Plant diseases are the primary cause of crop losses globally, which have an impact on the
world economy. To deal with these issues, new agriculture solutions are evolving that …

[HTML][HTML] SLViT: Shuffle-convolution-based lightweight Vision transformer for effective diagnosis of sugarcane leaf diseases

X Li, X Li, S Zhang, G Zhang, M Zhang… - Journal of King Saud …, 2023 - Elsevier
Farmers must accurately and promptly identify sugarcane leaf diseases with identical
symptoms. RGB images have a beneficial function in disease identification. Nevertheless …

A general-purpose edge-feature guidance module to enhance vision transformers for plant disease identification

B Chang, Y Wang, X Zhao, G Li, P Yuan - Expert Systems with Applications, 2024 - Elsevier
As agricultural applications are specialized, plant diseases are diverse, and there is a lack of
agricultural datasets, current plant disease identification performance is inadequate. In this …

Transfer learning and fine‐tuned transfer learning methods' effectiveness analyse in the CNN‐based deep learning models

C Öztürk, M Taşyürek… - … and Computation: Practice …, 2023 - Wiley Online Library
Object detection is a type of application that includes computer vision and image processing
technologies, which deal with detecting, tracking, and classifying desired objects in images …