AIMC Topic: Plant Weeds

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Testing the ability of unmanned aerial systems and machine learning to map weeds at subfield scales: a test with the weed Alopecurus myosuroides (Huds).

Pest management science May 21, 2019
BACKGROUND: It is important to map agricultural weed populations to improve management and maintain future food security. Advances in data collection and statistical methodology have created new opportunities to aid in the mapping of weed populations...
Remote Sensing Technology Poaceae United Kingdom Machine Learning Plant Weeds Geographic Mapping Weed Control
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Recognition pest by image-based transfer learning.

Journal of the science of food and agriculture Apr 22, 2019
BACKGROUND: Plant pests mainly refers to insects and mites that harm crops and products. There are a wide variety of plant pests, with wide distribution, fast reproduction and large quantity, which directly causes serious losses to crops. Therefore, ...
Pest Control Animals Humans Image Processing, Computer-Assisted Neural Networks, Computer Plant Weeds Machine Learning Plant Diseases Insecta Weed Control Crops, Agricultural
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Fully convolutional network for rice seedling and weed image segmentation at the seedling stage in paddy fields.

PloS one Apr 18, 2019
To reduce the cost of production and the pollution of the environment that is due to the overapplication of herbicide in paddy fields, the location information of rice seedlings and weeds must be detected in site-specific weed management (SSWM). With...
Neural Networks, Computer Oryza Crop Production Image Processing, Computer-Assisted Seedlings Plant Weeds
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Detection of broadleaf weeds growing in turfgrass with convolutional neural networks.

Pest management science Mar 8, 2019
BACKGROUND: Weed infestations reduce turfgrass aesthetics and uniformity. Postemergence (POST) herbicides are applied uniformly on turfgrass, hence areas without weeds are also sprayed. Deep learning, particularly the architecture of convolutional ne...
Neural Networks, Computer Deep Learning Plant Weeds Weed Control Cynodon
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Spectral Identification of Disease in Weeds Using Multilayer Perceptron with Automatic Relevance Determination.

Sensors (Basel, Switzerland) Aug 23, 2018
, a smut fungus, is studied as an agent for the biological control of (milk thistle) weed. Confirmation of the systemic infection is essential in order to assess the effectiveness of the biological control application and assist decision-making. Non...
Biological Control Agents Silybum marianum Plant Diseases Spectrum Analysis Basidiomycota Neural Networks, Computer Algorithms Plant Weeds
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An efficient swarm intelligence approach to feature selection based on invasive weed optimization: Application to multivariate calibration and classification using spectroscopic data.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jan 12, 2018
Variable selection plays a key role in classification and multivariate calibration. Variable selection methods are aimed at choosing a set of variables, from a large pool of available predictors, relevant to the analyte concentrations estimation, or ...
Calibration Gasoline Introduced Species Least-Squares Analysis Triticum Wine Artificial Intelligence Algorithms Plant Weeds
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A Multi-Robot Sense-Act Approach to Lead to a Proper Acting in Environmental Incidents.

Sensors (Basel, Switzerland) Aug 10, 2016
Many environmental incidents affect large areas, often in rough terrain constrained by natural obstacles, which makes intervention difficult. New technologies, such as unmanned aerial vehicles, may help address this issue due to their suitability to ...
Humans Software Agriculture Aircraft Herbicides Wireless Technology Environmental Monitoring Robotics Plant Weeds
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Modeling and optimization of anaerobic codigestion of potato waste and aquatic weed by response surface methodology and artificial neural network coupled genetic algorithm.

Bioresource technology Apr 19, 2016
A novel approach to overcome the acidification problem has been attempted in the present study by codigesting industrial potato waste (PW) with Pistia stratiotes (PS, an aquatic weed). The effectiveness of codigestion of the weed and PW was tested in...
Analysis of Variance Waste Products Biotechnology Anaerobiosis Fatty Acids, Volatile Hydrogen-Ion Concentration Aquatic Organisms Solanum tuberosum Biofuels Models, Theoretical Regression Analysis Plant Weeds Neural Networks, Computer Algorithms Reproducibility of Results
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Efficiently deep learning for monitoring in the wild.

Mathematical biosciences and engineering : MBE Jan 11, 2021
are an invasive weed which has caused serious harm to the biodiversity and stability of the ecosystem. It is very important to accurately and rapidly identifying and monitoring in the wild for managements taking the necessary strategies to control ...
Ecosystem Deep Learning Plant Weeds Ipomoea Artificial Intelligence
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Technology: The Future of Agriculture.

Nature Apr 26, 2017
Mobile Applications Agriculture Monitoring, Physiologic Robotics Plant Weeds Remote Sensing Technology Animal Husbandry Animal Diseases Time Factors Soil Animals Livestock Lasers Abattoirs Clinical Alarms Crop Production Agrochemicals Technology Transfer Depth Perception Pesticides Plant Diseases Automation Fruit Quality Control Vegetables Machine Learning
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