Leaf disease detection using machine learning and deep learning: Review and challenges
Identification of leaf disorder plays an important role in the economic prosperity of any
country. Many parts of a plant can be infected by a virus, fungal, bacteria, and other …
country. Many parts of a plant can be infected by a virus, fungal, bacteria, and other …
State of the art in flexible SERS sensors toward label-free and onsite detection: from design to applications
Surface-enhanced Raman scattering (SERS) as a powerful non-invasive spectroscopic
technique has been intensively used in bio/chemical sensing, enabling ultrasensitive …
technique has been intensively used in bio/chemical sensing, enabling ultrasensitive …
Deep learning system for paddy plant disease detection and classification
Automatic detection and analysis of rice crop diseases is widely required in the farming
industry, which can be utilized to avoid squandering financial and other resources, reduce …
industry, which can be utilized to avoid squandering financial and other resources, reduce …
A novel multi-head CNN design to identify plant diseases using the fusion of RGB images
Plant diseases and insect pests cause a significant threat to agricultural production. Early
detection and diagnosis of these diseases are critical and can reduce economic losses. The …
detection and diagnosis of these diseases are critical and can reduce economic losses. The …
Lightweight detection networks for tea bud on complex agricultural environment via improved YOLO v4
Rapid and accurate detection of tender tea buds in the natural tea garden environment is the
basis for intelligent tea picking. However, complex models result in high hardware …
basis for intelligent tea picking. However, complex models result in high hardware …
Pre-trained deep neural network-based features selection supported machine learning for rice leaf disease classification
Rice is a staple food for roughly half of the world's population. Some farmers prefer rice
cultivation to other crops because rice can thrive in a wide range of environments. Several …
cultivation to other crops because rice can thrive in a wide range of environments. Several …
An optimal hybrid multiclass SVM for plant leaf disease detection using spatial Fuzzy C-Means model
SK Sahu, M Pandey - Expert systems with applications, 2023 - Elsevier
In recent times, plant disease detection and diagnosing measures become a major concern
in the agriculture field. Earlier identification of plant disease aids the farmers to take …
in the agriculture field. Earlier identification of plant disease aids the farmers to take …
Lightweight federated learning for rice leaf disease classification using non independent and identically distributed images
Rice (Oryza sativa L.) is a vital food source all over the world, contributing 15% of the protein
and 21% of the energy intake per person in Asia, where most rice is produced and …
and 21% of the energy intake per person in Asia, where most rice is produced and …
Development of deep learning methodology for maize seed variety recognition based on improved swin transformer
C Bi, N Hu, Y Zou, S Zhang, S Xu, H Yu - Agronomy, 2022 - mdpi.com
In order to solve the problems of high subjectivity, frequent error occurrence and easy
damage of traditional corn seed identification methods, this paper combines deep learning …
damage of traditional corn seed identification methods, this paper combines deep learning …
DFN-PSAN: Multi-level deep information feature fusion extraction network for interpretable plant disease classification
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 …
intelligent and modernized agricultural production, as well as to reduce the use of pesticides …