AIMC Topic: Agriculture

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Region-aggregated attention CNN for disease detection in fruit images.

PloS one Oct 25, 2021
BACKGROUND: Diseases and pests have a profound effect on a yearly harvest and productivity in agriculture. A precise and accurate detection of the diseases and pests could facilitate timely treatment and management of the diseases and pests and lesse...
Agriculture Neural Networks, Computer Image Processing, Computer-Assisted Plant Diseases Humans Fruit
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A weighted twin support vector machine as a potential discriminant analysis tool and evaluation of its performance for near-infrared spectroscopic discrimination of the geographical origins of diverse agricultural products.

Talanta Oct 14, 2021
A weighted twin support vector machine (wTWSVM) was proposed as a potential discriminant analysis tool and its utility was evaluated for near-infrared (NIR) spectroscopic identification of the geographical origins of 12 different agricultural product...
Spectroscopy, Near-Infrared Support Vector Machine Least-Squares Analysis Geography Discriminant Analysis Agriculture
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Accurate Wheat Lodging Extraction from Multi-Channel UAV Images Using a Lightweight Network Model.

Sensors (Basel, Switzerland) Oct 14, 2021
The extraction of wheat lodging is of great significance to post-disaster agricultural production management, disaster assessment and insurance subsidies. At present, the recognition of lodging wheat in the actual complex field environment still has ...
Triticum Neural Networks, Computer Agriculture
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Weed Classification Using Explainable Multi-Resolution Slot Attention.

Sensors (Basel, Switzerland) Oct 9, 2021
In agriculture, explainable deep neural networks (DNNs) can be used to pinpoint the discriminative part of weeds for an imagery classification task, albeit at a low resolution, to control the weed population. This paper proposes the use of a multi-la...
Neural Networks, Computer Plant Weeds Attention Seedlings Agriculture
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Editorial: Special Issue "Implementation of Sensors and Artificial Intelligence for Environmental Hazards Assessment in Urban, Agriculture and Forestry Systems".

Sensors (Basel, Switzerland) Sep 24, 2021
Artificial intelligence (AI), together with robotics, sensors, sensor networks, internet of things (IoT) and machine/deep learning modeling, has reached the forefront towards the goal of increased efficiency in a multitude of application and purpose ...
Machine Learning Agriculture Artificial Intelligence Forestry Internet of Things
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Predicting rice yield at pixel scale through synthetic use of crop and deep learning models with satellite data in South and North Korea.

The Science of the total environment Aug 19, 2021
Prediction of rice yields at pixel scale rather than county scale can benefit crop management and scientific understanding because it is useful for monitoring how crop yields respond to various agricultural systems and environmental factors. In this ...
Democratic People's Republic of Korea Deep Learning Neural Networks, Computer Oryza Agriculture
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Quantitative estimation of soil properties using hybrid features and RNN variants.

Chemosphere Aug 17, 2021
Estimating soil properties is important for maximizing the production of crops in sustainable agriculture. The hyperspectral data next input depends upon the previous one, and the current techniques do not take advantage of this sequential nature of ...
Agriculture European Union Sand Neural Networks, Computer Soil
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Weakly Supervised Crop Area Segmentation for an Autonomous Combine Harvester.

Sensors (Basel, Switzerland) Jul 14, 2021
Machine vision with deep learning is a promising type of automatic visual perception for detecting and segmenting an object effectively; however, the scarcity of labelled datasets in agricultural fields prevents the application of deep learning to ag...
Agriculture Supervised Machine Learning Image Processing, Computer-Assisted Semantics
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Farm robots: ecological utopia or dystopia?

Trends in ecology & evolution Jul 13, 2021
Farm robots may lead to an ecological utopia where swarms of small robots help in overcoming the yield penalties and labor requirements associated with agroecological farming - or a dystopia with large robots cultivating monocultures. Societal discus...
Humans Agriculture Biodiversity Farms Robotics Utopias
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Deep Learning Based Prediction on Greenhouse Crop Yield Combined TCN and RNN.

Sensors (Basel, Switzerland) Jul 1, 2021
Currently, greenhouses are widely applied for plant growth, and environmental parameters can also be controlled in the modern greenhouse to guarantee the maximum crop yield. In order to optimally control greenhouses' environmental parameters, one ind...
Deep Learning Agriculture Algorithms Neural Networks, Computer Machine Learning
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