Artificial Intelligence and Smart Agriculture Applications
portes grátis
Artificial Intelligence and Smart Agriculture Applications
Podder, Prajoy; Bharati, Subrato; Mondal, M.Rubaiyat Hossain; Kose, Utku; Prasath, V.B. Surya
Taylor & Francis Ltd
10/2024
335
Mole
9781032318653
Pré-lançamento - envio 15 a 20 dias após a sua edição
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1. Application of Drone and Sensors in Advanced Farming: The Future Smart Farming Technology. 2. Development and Research of a Greenhouse Monitoring System. 3. A Cloud-Computing Model for Implementing Smart Agriculture. 4. Application of Conversational Artificial Intelligence for Farmer's Advisory and Communication. 5. The Use of an Intelligent Fuzzy Logic Controller to Predict the Global Warming Effect on Agriculture: The Case of Chickpea (Cicer arietinum L.) 6. Using Machine Learning Algorithms for Mapping Soil Macronutrient Elements Variability with Digital Environmental Data in an Alluvial Plain. 7. A Smart IoT Framework for Soil Fertility Enhancement Assisted via Deep Neural Networks. 8. Plant Disease Detection with the Help of Advanced Imaging Sensors. 9. Artificial Intelligence-Aided Phenomics in High throughput Stress Phenotyping of Plants. 10. Plant Disease Detection using Hybrid Deep Learning Architecture in Smart Agriculture Application. 11. Classification of Coffee Leaf Diseases through Image Processing Techniques. 12. The Use of Artificial Intelligence to Model Oil Extraction Yields from Seeds and Nuts. 13. Applications of Artificial Intelligence in Pest Management. 14. Applying Clustering Technique for Rainfall Received by Different District of Maharashtra State. 15. Predicting Rainfall for Aurangabad Division of Maharashtra by Applying Auto-Regressive Moving Average Model (ARIMA) Using Python Programming.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
AI;plant disease;pest management;global warming;neural networks;imaging;data science;sensors;CORINE Land Cover Class;fuzzy logic;Aster GDEM;RGB Sensor;Multiple Linear Regression;FLC.;Moisture Content;Soil Macronutrient;Soil Quality;Plant Disease Detection;NIR Band;Convolutional Neural;Pod Development Stage;Support Vector Regression;Smart Agriculture;Deep Learning Model;Membership Functions;Fuzzy Controller;RSM Model;Soil Fertility;Random Forest Algorithm;Stress Phenotyping;Deep Learning Algorithms;Data Set;Oil Extraction Yields
1. Application of Drone and Sensors in Advanced Farming: The Future Smart Farming Technology. 2. Development and Research of a Greenhouse Monitoring System. 3. A Cloud-Computing Model for Implementing Smart Agriculture. 4. Application of Conversational Artificial Intelligence for Farmer's Advisory and Communication. 5. The Use of an Intelligent Fuzzy Logic Controller to Predict the Global Warming Effect on Agriculture: The Case of Chickpea (Cicer arietinum L.) 6. Using Machine Learning Algorithms for Mapping Soil Macronutrient Elements Variability with Digital Environmental Data in an Alluvial Plain. 7. A Smart IoT Framework for Soil Fertility Enhancement Assisted via Deep Neural Networks. 8. Plant Disease Detection with the Help of Advanced Imaging Sensors. 9. Artificial Intelligence-Aided Phenomics in High throughput Stress Phenotyping of Plants. 10. Plant Disease Detection using Hybrid Deep Learning Architecture in Smart Agriculture Application. 11. Classification of Coffee Leaf Diseases through Image Processing Techniques. 12. The Use of Artificial Intelligence to Model Oil Extraction Yields from Seeds and Nuts. 13. Applications of Artificial Intelligence in Pest Management. 14. Applying Clustering Technique for Rainfall Received by Different District of Maharashtra State. 15. Predicting Rainfall for Aurangabad Division of Maharashtra by Applying Auto-Regressive Moving Average Model (ARIMA) Using Python Programming.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
AI;plant disease;pest management;global warming;neural networks;imaging;data science;sensors;CORINE Land Cover Class;fuzzy logic;Aster GDEM;RGB Sensor;Multiple Linear Regression;FLC.;Moisture Content;Soil Macronutrient;Soil Quality;Plant Disease Detection;NIR Band;Convolutional Neural;Pod Development Stage;Support Vector Regression;Smart Agriculture;Deep Learning Model;Membership Functions;Fuzzy Controller;RSM Model;Soil Fertility;Random Forest Algorithm;Stress Phenotyping;Deep Learning Algorithms;Data Set;Oil Extraction Yields
