AIMC Topic: Agriculture

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A lightweight deep learning model for multi-plant biotic stress classification and detection for sustainable agriculture.

Scientific reports Apr 9, 2025
Plant pathogens and pests hinder general plant health, resulting in poor agricultural yields and production. These threaten global food security and cause environmental and economic shortages. Amidst the available existing heavy deep learning (DL) mo...
Plant Diseases Stress, Physiological Agriculture Plant Leaves Neural Networks, Computer Deep Learning
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Novel hybrid transfer neural network for wheat crop growth stages recognition using field images.

Scientific reports Apr 7, 2025
Wheat is one of the world's most widely cultivated cereal crops and is a primary food source for a significant portion of the population. Wheat goes through several distinct developmental phases, and accurately identifying these stages is essential f...
Agriculture Triticum Crops, Agricultural Neural Networks, Computer Image Processing, Computer-Assisted
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Hybrid vision GNNs based early detection and protection against pest diseases in coffee plants.

Scientific reports Apr 6, 2025
Agriculture is an essential foundation that supports numerous economies, and the longevity of the coffee business is of paramount significance. Controlling and safeguarding coffee farms from harmful pests, including the Coffee Berry Borer, Mealybugs,...
Coffea Deep Learning Crops, Agricultural Agriculture Neural Networks, Computer Coffee Plant Diseases Animals Pest Control
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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...
Deep Learning India Plant Leaves Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Plant Weeds Agriculture Crops, Agricultural
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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...
Gossypium Crops, Agricultural Plant Diseases Artificial Intelligence Deep Learning Algorithms Agriculture
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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 Image Processing, Computer-Assisted Oryza Agriculture Plant Diseases Plant Leaves Artificial Intelligence Deep Learning
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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...
Deep Learning Agriculture Satellite Imagery Neural Networks, Computer Crops, Agricultural Soil
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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...
Machine Learning Soil Pollutants Probability Czech Republic Agriculture Environmental Monitoring Soil Farms
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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...
Remote Sensing Technology Biomass Machine Learning Agriculture Algorithms
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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...
Random Forest Crops, Agricultural Satellite Imagery Environmental Monitoring Support Vector Machine India Agriculture Machine Learning Algorithms
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