AIMC Topic: Agriculture

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Hybrid deep learning model for density and growth rate estimation on weed image dataset.

Scientific reports Apr 2, 2025
Agriculture research is particularly essential since crop production is a challenge for farmers in India and around the world. 37% of the crop is impacted by invasive plants (weeds). Those unwelcome plants that interbreed with cultivated crops and de...
Agriculture Plant Leaves Crops, Agricultural Plant Weeds Deep Learning India Image Processing, Computer-Assisted Neural Networks, Computer Algorithms
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Detection of cotton crops diseases using customized deep learning model.

Scientific reports Mar 28, 2025
The agricultural industry is experiencing revolutionary changes through the latest advances in artificial intelligence and deep learning-based technologies. These powerful tools are being used for a variety of tasks including crop yield estimation, c...
Crops, Agricultural Plant Diseases Gossypium Deep Learning Artificial Intelligence Agriculture Algorithms
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Artificial intelligence for sustainable farming with dual branch convolutional graph attention networks in rice leaf disease detection.

Scientific reports Mar 27, 2025
Rice is susceptible to various diseases, including brown spot, hispa, leaf smut, bacterial leaf blight, and leaf blast, all of which can negatively impact crop yields. Current disease detection methods encounter several challenges, such as reliance o...
Neural Networks, Computer Artificial Intelligence Plant Diseases Agriculture Plant Leaves Deep Learning Oryza Image Processing, Computer-Assisted
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Soil and crop interaction analysis for yield prediction with satellite imagery and deep learning techniques for the coastal regions.

Journal of environmental management Mar 25, 2025
Crop yield is a significant factor in world income and poverty alleviation as well as food production through agriculture. Conventional crop yield forecasting approaches that employ subjective estimates including farmers' perceptions are imprecise an...
Crops, Agricultural Satellite Imagery Neural Networks, Computer Soil Deep Learning Agriculture
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Machine learning for predictive mapping of exceedance probabilities for potentially toxic elements in Czech farmland.

Journal of environmental management Mar 24, 2025
For efficient decision-making and optimal land management trajectories, information on soil properties in relation to safety guidelines should be processed from point inventories to surface predictive maps. For large-scale predictive mapping, very fe...
Czech Republic Farms Agriculture Soil Pollutants Probability Environmental Monitoring Machine Learning Soil
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Integrating Proximal and Remote Sensing with Machine Learning for Pasture Biomass Estimation.

Sensors (Basel, Switzerland) Mar 22, 2025
This study tackles the challenge of accurately estimating pasture biomass by integrating proximal sensing, remote sensing, and machine learning techniques. Field measurements of vegetation height collected using the PaddockTrac ultrasonic sensor were...
Biomass Machine Learning Agriculture Algorithms Remote Sensing Technology
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Risk assessment of potentially toxic elements and mapping of groundwater pollution indices using soft computer models in an agricultural area, Northeast Algeria.

Journal of hazardous materials Mar 19, 2025
Groundwater (GW) quality and contamination by potentially toxic elements (PTEs) are major concerns for environmental sustainability, particularly in arid regions. The aim of this study was to assess the human health risks associated with GW contamina...
Risk Assessment Agriculture Groundwater Neural Networks, Computer Computer Simulation Linear Models Humans Metals, Heavy Environmental Monitoring Algeria Water Pollutants, Chemical
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Evaluating the performance of random forest, support vector machine, gradient tree boost, and CART for improved crop-type monitoring using greenest pixel composite in Google Earth Engine.

Environmental monitoring and assessment Mar 19, 2025
The development of machine learning algorithms, along with high-resolution satellite datasets, aids in improved agriculture monitoring and mapping. Nevertheless, the use of high-resolution optical satellite datasets is usually constrained by clouds a...
Algorithms India Agriculture Random Forest Machine Learning Environmental Monitoring Crops, Agricultural Support Vector Machine Satellite Imagery
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How monitoring crops and drought, combined with climate projections, enhances food security: Insights from the Northwestern regions of Bangladesh.

Environmental monitoring and assessment Mar 19, 2025
Crop and drought monitoring are vital for sustainable agriculture, as they ensure optimal crop growth, identify stress factors, and enhance productivity, all of which contribute to food security. However, climate projections are equally important as ...
Climate Bangladesh Climate Change Agriculture Food Security Droughts Crops, Agricultural Environmental Monitoring
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Incremental and transformational climate change adaptation factors in agriculture worldwide: A comparative analysis using natural language processing.

PloS one Mar 19, 2025
Climate change is projected to adversely affect agriculture worldwide. This requires farmers to adapt incrementally already early in the twenty-first century, and to pursue transformational adaptation to endure future climate-induced damages. Many ar...
Climate Change Farmers Adaptation, Physiological Agriculture Natural Language Processing Humans
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