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Agricultural Productivity: An AI-Based Crop Yield Prediction System Using Climate and Soil Data
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/s41976-024-00161-9openalex-extracted
Sustainable Agriculture and Climate Change: A Deep Learning Approach to Remote Sensing for Food Security Monitoring
inferredcites →https://doi.org/10.1007/s44246-024-00125-0openalex-extracted
Machine learning for persistent free radicals in biochar: dual prediction of contents and types using regression and classification models
inferredcites →https://doi.org/10.1016/j.atech.2024.100718openalex-extracted
Crop yield prediction using machine learning: An extensive and systematic literature review
inferredcites →https://doi.org/10.1016/j.compag.2018.02.016openalex-extracted
Deep learning in agriculture: A survey
inferredcites →https://doi.org/10.1016/j.compag.2025.110018openalex-extracted
Developing machine learning models from multisourced real-world datasets to enhance smart-farming practices
inferredcites →https://doi.org/10.1016/j.marpolbul.2024.116942openalex-extracted
Comparison of conventional and machine learning regression models for accurate prediction of selected optical active components – A case study: The Gulf of Izmit
inferredcites →https://doi.org/10.1016/j.procs.2024.04.215openalex-extracted
Smart Agriculture using Ensemble Machine Learning Techniques in IoT Environment
inferredcites →https://doi.org/10.1038/s44264-025-00052-6openalex-extracted
Advanced machine learning for regional potato yield prediction: analysis of essential drivers
inferredcites →https://doi.org/10.1080/17538947.2024.2443470openalex-extracted
Remote sensing-based winter wheat yield estimation integrating machine learning and crop growth multi-scenario simulations
inferredcites →https://doi.org/10.1109/icicnis64247.2024.10823110openalex-extracted
Enhancing Agricultural Yield Predictions with Real-Time IoT Sensor Data and Machine Learning Integration
inferredcites →https://doi.org/10.1186/s12859-024-05970-9openalex-extracted
Improving crop production using an agro-deep learning framework in precision agriculture
inferredcites →https://doi.org/10.1186/s13677-024-00626-8openalex-extracted
Edge computing-oriented smart agricultural supply chain mechanism with auction and fuzzy neural networks
inferredcites →https://doi.org/10.1201/9781003508625-9openalex-extracted
Enhancing crop yield prediction accuracy through the application of gradient descent optimization algorithms
inferredcites →https://doi.org/10.12944/carj.12.1.22openalex-extracted
Optimizing Crop Yield Prediction: Data-Driven Analysis and Machine Learning Modeling Using USDA Datasets
inferredcites →https://doi.org/10.1504/ijsami.2025.143099openalex-extracted
Enhancing crop yield prediction through machine learning regression analysis
inferredcites →https://doi.org/10.1609/aaai.v31i1.11172openalex-extracted
Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing Data
inferredcites →https://doi.org/10.28991/esj-2024-08-02-024openalex-extracted
Agriculture 5.0 and Explainable AI for Smart Agriculture: A Scoping Review
inferredcites →https://doi.org/10.3389/fpls.2019.00621openalex-extracted
Crop Yield Prediction Using Deep Neural Networks
inferredcites →https://doi.org/10.3390/iot5040028openalex-extracted
Integrated Iot Approaches for Crop Recommendation and Yield-Prediction Using Machine-Learning
inferredcites →https://doi.org/10.3390/s25020543openalex-extracted
Integrating Remote Sensing and Soil Features for Enhanced Machine Learning-Based Corn Yield Prediction in the Southern US
inferredcites →https://doi.org/10.47852/bonviewaaes32021220openalex-extracted
Leveraging Deep Learning Techniques to Obtain Efficacious Segmentation Results
inferredcites →https://doi.org/10.1109/igarss52108.2023.10282318openalex-snapshot
Predicting Crop Yield with Machine Learning: An Extensive Analysis of Input Modalities and Models on a Field and Sub-Field Level
inferredcites →https://doi.org/10.48550/arxiv.1603.02754openalex-snapshot
XGBoost: A Scalable Tree Boosting System
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/s43621-026-04510-0openalex-snapshot
Geospatial methods for SDG aligned natural resource management through bibliometric and systematic review
inferred← citeshttps://doi.org/10.1109/access.2025.3646354openalex-snapshot
A Residual Recurrent Generative Adversarial Network Approach for Crop Yield Estimation and Fertilizer Optimization
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