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Image acquisition, preprocessing and classification of citrus fruit diseases: A systematic literature review
Different kinds of techniques are evaluated and analyzed for various classification models
for the detection of diseases of citrus fruits. This paper aims to systematically review the …
for the detection of diseases of citrus fruits. This paper aims to systematically review the …
[PDF][PDF] Artificial intelligence in agriculture: A literature survey
G Bannerjee, U Sarkar, S Das… - international Journal of …, 2018 - researchgate.net
This paper presents a comprehensive literature survey on the applications of artificial
intelligence techniques in agriculture. The domain of agriculture faces many challenges …
intelligence techniques in agriculture. The domain of agriculture faces many challenges …
Precision farming in modern agriculture
The science, art and practice of growing plants are called agriculture. The history of
agriculture began thousands of years ago. It began independently in various parts of the …
agriculture began thousands of years ago. It began independently in various parts of the …
Cassava disease recognition from low‐quality images using enhanced data augmentation model and deep learning
OO Abayomi‐Alli, R Damaševičius, S Misra… - Expert …, 2021 - Wiley Online Library
Improvement of deep learning algorithms in smart agriculture is important to support the
early detection of plant diseases, thereby improving crop yields. Data acquisition for …
early detection of plant diseases, thereby improving crop yields. Data acquisition for …
Detecting cassava mosaic disease using a deep residual convolutional neural network with distinct block processing
For people in develo** countries, cassava is a major source of calories and
carbohydrates. However, Cassava Mosaic Disease (CMD) has become a major cause of …
carbohydrates. However, Cassava Mosaic Disease (CMD) has become a major cause of …
[HTML][HTML] AI-driven framework for recognition of guava plant diseases through machine learning from DSLR camera sensor based high resolution imagery
Plant diseases can cause a considerable reduction in the quality and number of agricultural
products. Guava, well known to be the tropics' apple, is one significant fruit cultivated in …
products. Guava, well known to be the tropics' apple, is one significant fruit cultivated in …
Recognizing apple leaf diseases using a novel parallel real‐time processing framework based on MASK RCNN and transfer learning: An application for smart …
Effective recognition of fruit leaf diseases has a substantial impact on agro‐based
economies. Several fruit diseases exist that badly impact the yield and quality of fruits. A …
economies. Several fruit diseases exist that badly impact the yield and quality of fruits. A …
[HTML][HTML] A comprehensive review of external quality measurements of fruits and vegetables using nondestructive sensing technologies
Fruits and vegetables have always had a significant economic impact on human survival,
providing food security and boosting output with minimal input. This review focuses on an in …
providing food security and boosting output with minimal input. This review focuses on an in …
Hybridization of ResNet with YOLO classifier for automated paddy leaf disease recognition: An optimized model
G Ganesan, J Chinnappan - Journal of Field Robotics, 2022 - Wiley Online Library
Paddy is the most significant crop utilized by more than 2.6 billion people. The paddy crops
are affected by various diseases that are unidentified and reduced the production of crop …
are affected by various diseases that are unidentified and reduced the production of crop …
[HTML][HTML] Unravelling the use of artificial intelligence in management of insect pests
B Kariyanna, M Sowjanya - Smart Agricultural Technology, 2024 - Elsevier
As per the FAO, the insect pest causes 30 to 40 percent loss every year across the globe.
The identification, classification and management of insect pest is very important to avoid …
The identification, classification and management of insect pest is very important to avoid …