Results 1 to 10 of about 37,961 (191)
A CNN-RNN Framework for Crop Yield Prediction [PDF]
Frontiers in Plant Science, 2020 Crop yield prediction is extremely challenging due to its dependence on multiple factors such as crop genotype, environmental factors, management practices, and their interactions.
Saeed Khaki +2 more
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Crop Yield Prediction Using Deep Neural Networks [PDF]
Frontiers in Plant Science, 2019 Crop yield is a highly complex trait determined by multiple factors such as genotype, environment, and their interactions. Accurate yield prediction requires fundamental understanding of the functional relationship between yield and these interactive ...
Saeed Khaki, Lizhi Wang
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An interaction regression model for crop yield prediction [PDF]
Scientific Reports, 2021 Crop yield prediction is crucial for global food security yet notoriously challenging due to multitudinous factors that jointly determine the yield, including genotype, environment, management, and their complex interactions.
Javad Ansarifar +2 more
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A Comprehensive Review of Crop Yield Prediction Using Machine Learning Approaches With Special Emphasis on Palm Oil Yield Prediction [PDF]
IEEE Access, 2021 An early and reliable estimation of crop yield is essential in quantitative and financial evaluation at the field level for determining strategic plans in agricultural commodities for import-export policies and doubling farmer’s incomes.
Mamunur Rashid +4 more
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A Systematic Literature Review on Crop Yield Prediction with Deep Learning and Remote Sensing
Remote Sensing, 2022 Deep learning has emerged as a potential tool for crop yield prediction, allowing the model to automatically extract features and learn from the datasets. Meanwhile, smart farming technology enables the farmers to achieve maximum crop yield by extracting
Priyanga Muruganantham +4 more
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AI-enabled Barilai–Borwein–Blinder–Oaxaca–Bernoulli Deep Classifier for Enhanced Crop Yield Prediction [PDF]
Scientific ReportsThis article explores the integration of advanced Artificial Intelligence (AI) enabled deep learning methods with accurate crop yield prediction. The objective of the work is to enhance the accuracy, sensitivity, and specificity of crop yield prediction.
Rajesh Kumar Dhanaraj +3 more
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Deep Learning Based Prediction on Greenhouse Crop Yield Combined TCN and RNN
Sensors, 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.
Liyun Gong +4 more
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Crop Yield Prediction Using Deep Reinforcement Learning Model for Sustainable Agrarian Applications
IEEE Access, 2020 Predicting crop yield based on the environmental, soil, water and crop parameters has been a potential research topic. Deep-learning-based models are broadly used to extract significant crop features for prediction. Though these methods could resolve the
Dhivya Elavarasan +1 more
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Crop Yield Prediction in Precision Agriculture
Agronomy, 2022 Predicting crop yields is one of the most challenging tasks in agriculture. It plays an essential role in decision making at global, regional, and field levels. Soil, meteorological, environmental, and crop parameters are used to predict crop yield.
Anikó Nyéki, Miklós Neményi
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International Journal of Applied Earth Observations and Geoinformation, 2020 Large-scale crop yield prediction is critical for early warning of food insecurity, agricultural supply chain management, and economic market. Satellite-based Solar-Induced Chlorophyll Fluorescence (SIF) products have revealed hot spots of photosynthesis
Bin Peng +7 more
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