A comprehensive survey of few-shot learning: Evolution, applications, challenges, and opportunities
Few-shot learning (FSL) has emerged as an effective learning method and shows great
potential. Despite the recent creative works in tackling FSL tasks, learning valid information …
potential. Despite the recent creative works in tackling FSL tasks, learning valid information …
Plant disease detection and classification by deep learning—a review
L Li, S Zhang, B Wang - IEEE Access, 2021 - ieeexplore.ieee.org
Deep learning is a branch of artificial intelligence. In recent years, with the advantages of
automatic learning and feature extraction, it has been widely concerned by academic and …
automatic learning and feature extraction, it has been widely concerned by academic and …
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …
large amount of data to achieve exceptional performance. Unfortunately, many applications …
Performance of deep learning vs machine learning in plant leaf disease detection
Plants are recognized as essential as they are the primary source of humanity's energy
production since they are having nutritious, medicinal, etc. values. At any time between crop …
production since they are having nutritious, medicinal, etc. values. At any time between crop …
Review on convolutional neural network (CNN) applied to plant leaf disease classification
J Lu, L Tan, H Jiang - Agriculture, 2021 - mdpi.com
Crop production can be greatly reduced due to various diseases, which seriously endangers
food security. Thus, detecting plant diseases accurately is necessary and urgent. Traditional …
food security. Thus, detecting plant diseases accurately is necessary and urgent. Traditional …
A survey on using deep learning techniques for plant disease diagnosis and recommendations for development of appropriate tools
Several factors associated with disease diagnosis in plants using deep learning techniques
must be considered to develop a robust system for accurate disease management. A …
must be considered to develop a robust system for accurate disease management. A …
VGG-ICNN: A Lightweight CNN model for crop disease identification
Crop diseases cause a substantial loss in the quantum and quality of agricultural production.
Regular monitoring may help in early stage disease detection an d thereby reduction in crop …
Regular monitoring may help in early stage disease detection an d thereby reduction in crop …
Trends in vision-based machine learning techniques for plant disease identification: A systematic review
Globally, all the major crops are significantly affected by diseases every year, as manual
inspection across diverse fields is time-consuming, tedious, and requires expert knowledge …
inspection across diverse fields is time-consuming, tedious, and requires expert knowledge …
A review of deep learning in multiscale agricultural sensing
Population growth, climate change, and the worldwide COVID-19 pandemic are imposing
increasing pressure on global agricultural production. The challenge of increasing crop yield …
increasing pressure on global agricultural production. The challenge of increasing crop yield …
A novel deep learning method for detection and classification of plant diseases
The agricultural production rate plays a pivotal role in the economic development of a
country. However, plant diseases are the most significant impediment to the production and …
country. However, plant diseases are the most significant impediment to the production and …