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[HTML][HTML] Deep learning for rice leaf disease detection: A systematic literature review on emerging trends, methodologies and techniques
Rice is an essential food crop that is cultivated in many countries. Rice leaf diseases can
cause significant damage to crop cultivation, leading to reduced yields and economic …
cause significant damage to crop cultivation, leading to reduced yields and economic …
Plant disease detection and classification techniques: a comparative study of the performances
WB Demilie - Journal of Big Data, 2024 - Springer
One of the essential components of human civilization is agriculture. It helps the economy in
addition to supplying food. Plant leaves or crops are vulnerable to different diseases during …
addition to supplying food. Plant leaves or crops are vulnerable to different diseases during …
Advancements in rice disease detection through convolutional neural networks: A comprehensive review
B Gülmez - Heliyon, 2024 - cell.com
This review paper addresses the critical need for advanced rice disease detection methods
by integrating artificial intelligence, specifically convolutional neural networks (CNNs). Rice …
by integrating artificial intelligence, specifically convolutional neural networks (CNNs). Rice …
[HTML][HTML] Classification and detection of rice diseases using a 3-stage CNN architecture with transfer learning approach
Rice is a vital crop for global food security, but its production is vulnerable to various
diseases. Early detection and treatment of rice diseases are crucial to minimise yield losses …
diseases. Early detection and treatment of rice diseases are crucial to minimise yield losses …
Identification of rice leaf diseases and deficiency disorders using a novel DeepBatch technique
Rice is one of the most widely consumed foods all over the world. Various diseases and
deficiency disorders impact the rice crop's growth, thereby hampering the rice yield …
deficiency disorders impact the rice crop's growth, thereby hampering the rice yield …
E2ETCA: End-to-end training of CNN and attention ensembles for rice disease diagnosis1
Rice is one of the most important crops worldwide. Diseases of the rice plant can drastically
reduce crop yield and even lead to complete loss of production. Early diagnosis can reduce …
reduce crop yield and even lead to complete loss of production. Early diagnosis can reduce …
A deep learning-based model for biotic rice leaf disease detection
The detection of rice leaf disease is an essential step for implementing precise and timely
interventions, thereby mitigating the spread and minimizing the ecological and economic …
interventions, thereby mitigating the spread and minimizing the ecological and economic …
A systematic review of deep learning applications for rice disease diagnosis: current trends and future directions
Background The occurrence of diseases in rice leaves presents a substantial challenge to
farmers on a global scale, hence jeopardizing the food security of an expanding global …
farmers on a global scale, hence jeopardizing the food security of an expanding global …
A robust and light-weight transfer learning-based architecture for accurate detection of leaf diseases across multiple plants using less amount of images
Leaf diseases are a global threat to crop production and food preservation. Detecting these
diseases is crucial for effective management. We introduce LeafDoc-Net, a robust …
diseases is crucial for effective management. We introduce LeafDoc-Net, a robust …
Development of deep and machine learning convolutional networks of variable spatial resolution for automatic detection of leaf blast disease of rice
G Kaur, JS Sivia - Computers and Electronics in Agriculture, 2024 - Elsevier
The widespread prevalence of leaf blast disease poses a significant threat to rice (Oryza
sativa L.) ecosystems globally, and inflicts substantial grain yield losses. The pervasive …
sativa L.) ecosystems globally, and inflicts substantial grain yield losses. The pervasive …