A survey of deep convolutional neural networks applied for prediction of plant leaf diseases
In the modern era, deep learning techniques have emerged as powerful tools in image
recognition. Convolutional Neural Networks, one of the deep learning tools, have attained …
recognition. Convolutional Neural Networks, one of the deep learning tools, have attained …
A review of deep learning techniques used in agriculture
Deep learning (DL) is a robust data-analysis and image-processing technique that has
shown great promise in the agricultural sector. In this study, 129 papers that are based on …
shown great promise in the agricultural sector. In this study, 129 papers that are based on …
Recognition of leaf disease using hybrid convolutional neural network by applying feature reduction
Agriculture is crucial to the economic prosperity and development of India. Plant diseases
can have a devastating influence towards food safety and a considerable loss in the …
can have a devastating influence towards food safety and a considerable loss in the …
[HTML][HTML] Deep learning based computer vision approaches for smart agricultural applications
VG Dhanya, A Subeesh, NL Kushwaha… - Artificial Intelligence in …, 2022 - Elsevier
The agriculture industry is undergoing a rapid digital transformation and is growing powerful
by the pillars of cutting-edge approaches like artificial intelligence and allied technologies …
by the pillars of cutting-edge approaches like artificial intelligence and allied technologies …
[HTML][HTML] Computer vision in smart agriculture and precision farming: Techniques and applications
The transformation of age-old farming practices through the integration of digitization and
automation has sparked a revolution in agriculture that is driven by cutting-edge computer …
automation has sparked a revolution in agriculture that is driven by cutting-edge computer …
A Hybrid Model for Leaf Diseases Classification Based on the Modified Deep Transfer Learning and Ensemble Approach for Agricultural AIoT‐Based Monitoring
M Saberi Anari - Computational Intelligence and Neuroscience, 2022 - Wiley Online Library
As possible diseases develop on plant leaves, classification is constantly hampered by
obstacles such as overfitting and low accuracy. To distinguish healthy products from …
obstacles such as overfitting and low accuracy. To distinguish healthy products from …
Application of drone surveillance for advance agriculture monitoring by Android application using convolution neural network
Plant diseases are a significant threat to global food security, impacting crop yields and
economic growth. Accurate identification of plant diseases is crucial to minimize crop loses …
economic growth. Accurate identification of plant diseases is crucial to minimize crop loses …
A survey on deep learning and its impact on agriculture: Challenges and opportunities
M Albahar - Agriculture, 2023 - mdpi.com
The objective of this study was to provide a comprehensive overview of the recent
advancements in the use of deep learning (DL) in the agricultural sector. The author …
advancements in the use of deep learning (DL) in the agricultural sector. The author …
Deep learning approaches and interventions for futuristic engineering in agriculture
With shrinking natural resources and the climate challenges, it is foreseen that there will be
an imminent stress in agricultural outputs. Deep learning provides immense possibilities in …
an imminent stress in agricultural outputs. Deep learning provides immense possibilities in …
Machine learning for plant stress modeling: A perspective towards hormesis management
Plant stress is one of the most significant factors affecting plant fitness and, consequently,
food production. However, plant stress may also be profitable since it behaves hormetically; …
food production. However, plant stress may also be profitable since it behaves hormetically; …