Sustainable Farming through Machine Learning
portes grátis
Sustainable Farming through Machine Learning
Enhancing Productivity and Efficiency
Yang, Ming; Kumar Paikaray, Bijay; Satpathy, Suneeta; Balakrishnan, Arunkumar
Taylor & Francis Ltd
11/2024
284
Dura
9781032777498
Pré-lançamento - envio 15 a 20 dias após a sua edição
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1. Exploring AI and ML Strategies for Crop Health Monitoring and Management. 2. Enhancing Crop Productivity by Suitable Crop Prediction Using Cutting-Edge Technologies. 3. Crop Yield Prediction Using Machine Learning Random Forest Algorithm. 4. A multi-objective based genetic approach for increasing crop yield on sustainable farming. 5. Drones For Crop Monitoring And Analysis. 6. Decision Support System For Sustainable Farming. 7. Empowering Agriculture: Harnessing the Potential of AI-Driven Virtual Tutors for Farmer Education and Investment Strategies. 8. Enhancing Agricultural Ecosystem Surveillance through Autonomous Sensor Networks. 9. Crop Disease Detection Using Image Analysis. 10. Automated Detection of Plant Diseases Utilizing Convolutional Neural Networks. 11. Apple Leaves Diseases Detection Using Deep Learning. 12.Optimizing Agricultural Yield: Comprehensive Approaches for Recommendation System in Precision Agriculture. 13. Advancements in Precision Agriculture: A Machine Learning-based Approach for Crop Management Optimization. 14. Precision Agriculture with Remote Sensing: Integrating Deep Learning for Crop Monitoring. 15. Farmers Guide: Data-Driven Crop Recommendations for Precision and Sustainable Agriculture Using IoT and ML. 16. Application of Machine Learning in the Analysis and Prediction of Animal Disease. 17. Transforming Indian Agriculture: A Machine Learning Approach for Informed Decision-Making and Sustainable Crop Recommendations. 18. Automated Detection of Water Quality for Smart Systems using Various Sampling Techniques - An Agricultural Perspective. 19. Scope of Artificial Intelligence (A.I.) in "Agriculture Sector and its applicability in Farm Mechanization in Odisha. 20. Ethical Considerations and Social Implications.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
AI technology in farming;AI/ML farming;AI/ML for plant disease detection;Agricultural automation with AI;Agricultural robotics;Crop monitoring using AI/ML;Livestock management with ML;ML applications in agriculture;Machine learning for farming;Precision agriculture and AI/ML
1. Exploring AI and ML Strategies for Crop Health Monitoring and Management. 2. Enhancing Crop Productivity by Suitable Crop Prediction Using Cutting-Edge Technologies. 3. Crop Yield Prediction Using Machine Learning Random Forest Algorithm. 4. A multi-objective based genetic approach for increasing crop yield on sustainable farming. 5. Drones For Crop Monitoring And Analysis. 6. Decision Support System For Sustainable Farming. 7. Empowering Agriculture: Harnessing the Potential of AI-Driven Virtual Tutors for Farmer Education and Investment Strategies. 8. Enhancing Agricultural Ecosystem Surveillance through Autonomous Sensor Networks. 9. Crop Disease Detection Using Image Analysis. 10. Automated Detection of Plant Diseases Utilizing Convolutional Neural Networks. 11. Apple Leaves Diseases Detection Using Deep Learning. 12.Optimizing Agricultural Yield: Comprehensive Approaches for Recommendation System in Precision Agriculture. 13. Advancements in Precision Agriculture: A Machine Learning-based Approach for Crop Management Optimization. 14. Precision Agriculture with Remote Sensing: Integrating Deep Learning for Crop Monitoring. 15. Farmers Guide: Data-Driven Crop Recommendations for Precision and Sustainable Agriculture Using IoT and ML. 16. Application of Machine Learning in the Analysis and Prediction of Animal Disease. 17. Transforming Indian Agriculture: A Machine Learning Approach for Informed Decision-Making and Sustainable Crop Recommendations. 18. Automated Detection of Water Quality for Smart Systems using Various Sampling Techniques - An Agricultural Perspective. 19. Scope of Artificial Intelligence (A.I.) in "Agriculture Sector and its applicability in Farm Mechanization in Odisha. 20. Ethical Considerations and Social Implications.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
