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Deep learning: systematic review, models, challenges, and research directions
T Talaei Khoei, H Ould Slimane… - Neural Computing and …, 2023 - Springer
The current development in deep learning is witnessing an exponential transition into
automation applications. This automation transition can provide a promising framework for …
automation applications. This automation transition can provide a promising framework for …
[HTML][HTML] Machine learning in nutrient management: A review
In agriculture, precise fertilization and effective nutrient management are critical. Machine
learning (ML) has recently been increasingly used to develop decision support tools for …
learning (ML) has recently been increasingly used to develop decision support tools for …
[HTML][HTML] DeepCrop: Deep learning-based crop disease prediction with web application
Agriculture plays a significant role in every nation's economy by producing crops. Plant
disease identification is one of the most important aspects of maintaining an agriculturally …
disease identification is one of the most important aspects of maintaining an agriculturally …
A two-stage deep-learning based segmentation model for crop disease quantification based on corn field imagery
It is important to develop accurate disease management systems to identify and segment
corn disease lesions and estimate their severity under complex field conditions. Although …
corn disease lesions and estimate their severity under complex field conditions. Although …
Toward generalization of deep learning-based plant disease identification under controlled and field conditions
Identifying corn diseases under field conditions is crucial for implementing effective disease
management systems. Deep learning (DL)-based plant disease identification using deep …
management systems. Deep learning (DL)-based plant disease identification using deep …
A deep features extraction model based on the transfer learning model and vision transformer “tlmvit” for plant disease classification
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 …
plant leaves. The agriculture industry is negatively impacted by plant diseases causing crop …
Monitoring tomato leaf disease through convolutional neural networks
Agriculture plays an essential role in Mexico's economy. The agricultural sector has a 2.5%
share of Mexico's gross domestic product. Specifically, tomatoes have become the country's …
share of Mexico's gross domestic product. Specifically, tomatoes have become the country's …
PMVT: a lightweight vision transformer for plant disease identification on mobile devices
Due to the constraints of agricultural computing resources and the diversity of plant
diseases, it is challenging to achieve the desired accuracy rate while kee** the network …
diseases, it is challenging to achieve the desired accuracy rate while kee** the network …
[HTML][HTML] Plant disease diagnosis using deep learning based on aerial hyperspectral images: A review
Plant diseases cause considerable economic loss in the global agricultural industry. A
current challenge in the agricultural industry is the development of reliable methods for …
current challenge in the agricultural industry is the development of reliable methods for …
MaizeNet: A deep learning approach for effective recognition of maize plant leaf diseases
The presence of various maize plant leaf diseases has significantly decreased both the
quality and quantity of crop production. In order to take the appropriate steps to prevent the …
quality and quantity of crop production. In order to take the appropriate steps to prevent the …