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On using artificial intelligence and the internet of things for crop disease detection: A contemporary survey
The agricultural sector remains a key contributor to the Moroccan economy, representing
about 15% of gross domestic product (GDP). Disease attacks are constant threats to …
about 15% of gross domestic product (GDP). Disease attacks are constant threats to …
Deep learning for plant identification and disease classification from leaf images: multi-prediction approaches
Deep learning (DL) plays an important role in modern agriculture, especially in plant
pathology using leaf images where convolutional neural networks (CNN) are attracting a lot …
pathology using leaf images where convolutional neural networks (CNN) are attracting a lot …
[HTML][HTML] Plant leaf disease detection using computer vision and machine learning algorithms
SS Harakannanavar, JM Rudagi… - Global Transitions …, 2022 - Elsevier
Agriculture provides food to all the human beings even in case of rapid increase in the
population. It is recommended to predict the plant diseases at their early stage in the field of …
population. It is recommended to predict the plant diseases at their early stage in the field of …
A comparative analysis of machine learning algorithms for detection of organic and nonorganic cotton diseases
Cotton is the natural fiber produced, and the commercial crop grown in monoculture on 2.5%
of total agricultural land. Cotton is a drought‐resistant crop that provides a reliable income to …
of total agricultural land. Cotton is a drought‐resistant crop that provides a reliable income to …
Machine learning for leaf disease classification: data, techniques and applications
The growing demand for sustainable development brings a series of information
technologies to help agriculture production. Especially, the emergence of machine learning …
technologies to help agriculture production. Especially, the emergence of machine learning …
Leaf disease detection and classification
BV Nikith, NKS Keerthan, MS Praneeth… - Procedia Computer …, 2023 - Elsevier
The notion of smart farming is gaining traction in the agricultural industry these days, and it
makes use of sensors and a variety of machine learning based technologies. According to …
makes use of sensors and a variety of machine learning based technologies. According to …
A review of machine learning techniques in agroclimatic studies
The interplay of machine learning (ML) and deep learning (DL) within the agroclimatic
domain is pivotal for addressing the multifaceted challenges posed by climate change on …
domain is pivotal for addressing the multifaceted challenges posed by climate change on …
Secure and Smart Trolley Shop** System based on IoT Module
There are several ways in which the Internet of Things (IoT) is changing people's lives. An
intelligent shop** system, for example, may link all of a grocery store's products. When an …
intelligent shop** system, for example, may link all of a grocery store's products. When an …
AI-Inspired Algorithms for the Diagnosis of Diseases in Cotton Plant
Cotton is a monoculture crop planted on 2.5% of agricultural land. Cotton is drought-
resistant and gives farmers in climate-change-prone areas a steady income. These cotton …
resistant and gives farmers in climate-change-prone areas a steady income. These cotton …
Hybrid attention network for citrus disease identification
Accurate identification and timely prevention of citrus diseases will effectively protect the
interests of the citrus industry. However, the citrus disease identification models currently …
interests of the citrus industry. However, the citrus disease identification models currently …