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The power of data : driving climate change with data science and artificial intelligence innovations / / edited by Aboul Ella Hassanien and Ashraf Darwish
| The power of data : driving climate change with data science and artificial intelligence innovations / / edited by Aboul Ella Hassanien and Ashraf Darwish |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (255 pages) |
| Disciplina | 060 |
| Collana | Studies in Big Data |
| Soggetto topico |
Artificial intelligence
Environmental protection - Data processing Green technology - Technological innovations |
| ISBN | 3-031-22456-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part 1: Artificial Intelligence in climate change Applications -- Chapter 1. Artificial Intelligence for Predicting Floods: A Climatic Change Phenomenon -- Chapter 2. Prediction of Climate Change Impact based on Air Flight CO2 Emissions Using Machine Learning: Towards Green Air Flights -- Chapter 3. The Impact of Artificial Intelligence on Waste Management for Climate Change -- Chapter 4. A Machine Learning-based Model for Predicting Temperature under the Effects of Climate Change -- Part 2: Emerging Technologies in Industry and Energy Sector -- Chapter 5. Prediction of CO2 Emission in Cars using Machine Learning Algorithms -- Chapter 6. Climate change: the challenge of Tunisia and previsions for renewable energy production -- Chapter 7. Clean Energy Management based on Internet of Things and Sensor Networks for Climate Change Problems -- Chapter 8. Digital Twin Technology for Energy Management Systems to Tackle Climate Change Challenges -- Chapter 9. The Role of Internet of Things in Mitigating the Effect of Climate Change: Case study: An ozone prediction model -- Part 3: Emerging Climate Change Technology in Agriculture Sector -- Chapter 10. Optimized Multi-Kernel Predictive Model for the Crop Prediction with Climate Factors and Soil Properties Optimized Multi-Kernel Predictive Model for the Crop Prediction with Climate Factors and Soil Properties -- Chapter 11. An Intelligent Crop Recommendation Model for the Three Strategic Crops in Egypt based on Climate Change Data -- Chapter 12. Cost Effective Decision Support System for Smart Water Management System -- Chapter 13. The Role of Artificial Intelligence in Water Management in Agriculture for Climate Change Impacts -- Part 4: Emerging Climate Change Technologies in Healthcare Sector -- Chapter 14. The Influence of Climate Change on the Re-Emergence of Malaria Using Artificial Intelligence. |
| Record Nr. | UNINA-9910682591903321 |
| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The power of data : driving climate change with data science and artificial intelligence innovations / / edited by Aboul Ella Hassanien and Ashraf Darwish
| The power of data : driving climate change with data science and artificial intelligence innovations / / edited by Aboul Ella Hassanien and Ashraf Darwish |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (255 pages) |
| Disciplina | 060 |
| Collana | Studies in Big Data |
| Soggetto topico |
Artificial intelligence
Environmental protection - Data processing Green technology - Technological innovations |
| ISBN | 3-031-22456-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part 1: Artificial Intelligence in climate change Applications -- Chapter 1. Artificial Intelligence for Predicting Floods: A Climatic Change Phenomenon -- Chapter 2. Prediction of Climate Change Impact based on Air Flight CO2 Emissions Using Machine Learning: Towards Green Air Flights -- Chapter 3. The Impact of Artificial Intelligence on Waste Management for Climate Change -- Chapter 4. A Machine Learning-based Model for Predicting Temperature under the Effects of Climate Change -- Part 2: Emerging Technologies in Industry and Energy Sector -- Chapter 5. Prediction of CO2 Emission in Cars using Machine Learning Algorithms -- Chapter 6. Climate change: the challenge of Tunisia and previsions for renewable energy production -- Chapter 7. Clean Energy Management based on Internet of Things and Sensor Networks for Climate Change Problems -- Chapter 8. Digital Twin Technology for Energy Management Systems to Tackle Climate Change Challenges -- Chapter 9. The Role of Internet of Things in Mitigating the Effect of Climate Change: Case study: An ozone prediction model -- Part 3: Emerging Climate Change Technology in Agriculture Sector -- Chapter 10. Optimized Multi-Kernel Predictive Model for the Crop Prediction with Climate Factors and Soil Properties Optimized Multi-Kernel Predictive Model for the Crop Prediction with Climate Factors and Soil Properties -- Chapter 11. An Intelligent Crop Recommendation Model for the Three Strategic Crops in Egypt based on Climate Change Data -- Chapter 12. Cost Effective Decision Support System for Smart Water Management System -- Chapter 13. The Role of Artificial Intelligence in Water Management in Agriculture for Climate Change Impacts -- Part 4: Emerging Climate Change Technologies in Healthcare Sector -- Chapter 14. The Influence of Climate Change on the Re-Emergence of Malaria Using Artificial Intelligence. |
| Record Nr. | UNISA-996547968103316 |
| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Proceedings of Second Doctoral Symposium on Computational Intelligence : DoSCI 2021
| Proceedings of Second Doctoral Symposium on Computational Intelligence : DoSCI 2021 |
| Autore | Gupta Deepak |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2021 |
| Descrizione fisica | 1 online resource (902 pages) |
| Altri autori (Persone) |
KhannaAshish
KansalVineet FortinoGiancarlo HassanienAboul Ella |
| Collana | Advances in Intelligent Systems and Computing Ser. |
| Soggetto genere / forma | Electronic books. |
| ISBN | 981-16-3346-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Proceedings of Second Doctoral Symposium on Computational Intelligence |
| Record Nr. | UNINA-9910502975803321 |
Gupta Deepak
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| Singapore : , : Springer Singapore Pte. Limited, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of the 8th international conference on advanced intelligent systems and informatics 2022 / / editors : Aboul Ella Hassanien [and four others]
| Proceedings of the 8th international conference on advanced intelligent systems and informatics 2022 / / editors : Aboul Ella Hassanien [and four others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (844 pages) |
| Disciplina | 006.3 |
| Collana | Lecture notes on data engineering and communications technologies |
| Soggetto topico | Artificial intelligence |
| ISBN | 3-031-20601-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Organization -- Preface -- Contents -- Machine Learning -- Anti-electricity Stealing Detection Based on Recurrent Neural Network -- 1 Introduction -- 2 Build the Model -- 3 Anti-stealing Algorithm Detection Implementations -- 3.1 Data Preprocessing -- 3.2 Anti-electricity Stealing Detection Based on Clustering Algorithm -- 3.3 Anti-theft Detection Based on BP Neural Network -- 4 Anti-electricity Stealing Detection Based on Recurrent Neural Network -- 5 Conclusion -- References -- Self-supervised Learning for Foreground Segmentation with a Few Amount of Labeled Images Using Transformers -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 ROAR-TR Architecture -- 3.2 ROAR-TR Training -- 4 Experiments and Results -- 4.1 Experiments Pre-training -- 4.2 Standard Foreground Segmentation Experiment -- 4.3 Few-Shot Foreground Segmentation Experiment -- 4.4 Ablation Study -- 5 Conclusion -- References -- Adaptive Collaborative Learning Process in a Hybrid Model -- 1 Introduction -- 2 Hybrid Learning -- 2.1 Benefits of Hybrid Learning -- 2.2 Challenges of Hybrid Learning -- 3 Proposed Model -- 4 Collaborative Learning -- 4.1 Collaborative Learning Scenario -- 4.2 Assignment of Roles -- 5 Numerical Results -- 6 Conclusion -- References -- Overview of Gradient Descent Algorithms: Application to Railway Regularity -- 1 Introduction -- 2 Context -- 3 Optimization Techniques -- 3.1 Gradient Descent Algorithm -- 3.2 Ordinary Gradient Descent -- 3.3 Gradient Descent Optimization Algorithm -- 4 Related Works -- 5 Case Study -- 5.1 Dataset Overview -- 5.2 Data Visualization -- 5.3 Results -- 6 Discussion of Simulation Results -- 7 Conclusion -- References -- Major Role of Artificial Intelligence, Machine Learning, and Deep Learning in Identity and Access Management Field: Challenges and State of the Art -- 1 Introduction -- 2 I&.
AM: Definitions and Background -- 2.1 Definition of I& -- AM and Its Processes -- 3 AI, Machine Learning, Deep Learning: Background, Basic Principles and Project Management Approach -- 3.1 Background and Basic Principles -- 3.2 Project Management Approach: CPMAI Methodology -- 4 AI, ML and DL in I& -- AM Field: The Main Challenges -- 4.1 Identification -- 4.2 Authentication -- 4.3 Authorization -- 4.4 Auditing and Monitoring -- 4.5 Accountability -- 5 AI in I& -- AM: A State of the Art -- 5.1 Identification -- 5.2 Authentication -- 5.3 Authorization -- 5.4 Auditing and Monitoring -- 5.5 Accountability -- 6 Discussion and Analysis -- 6.1 Identification -- 6.2 Authentication -- 6.3 Authorization -- 6.4 Auditing and Monitoring -- 6.5 Accountability -- 7 Challenges and Future Research Direction -- 8 Conclusion -- References -- Analysis of Feature Selection Methods for Network Traffic Classification -- 1 Introduction -- 2 Related Work -- 3 Background of Machine Learning and Feature Selection -- 3.1 Machine Learning -- 3.2 Feature Selection -- 4 The Proposed Method -- 4.1 Dataset -- 4.2 Architectures -- 4.3 Validation -- 5 Experimental Results -- 5.1 Encrypted Data -- 5.2 Non-encrypted data -- 6 Conclusion -- References -- MOOC Video Classification Using Natural Language Processing and Machine Learning Model -- 1 Introduction -- 2 Related Work -- 3 Proposed Framework -- 3.1 Build the Machine Learning Dataset -- 3.2 Model Training -- 3.3 Evaluating the Model -- 4 Experimentation and Results -- 5 Conclusion and Future Work -- References -- A Problem and Project-Based Learning Strategy to Promote Students' Motivation in Post-pandemic Graduation Design Studio: A Prospective Comparative Study -- 1 Introduction -- 2 Post Pandemic Graduation Design Studio -- 2.1 Nature of Graduation Design Studio -- 2.2 Stages of Graduation Design Process. 3 Fundamental Factors of PPBL Strategy in Design Studio -- 3.1 Concept of PPBL Strategy -- 3.2 Students' Motivation and PPBL Strategy -- 3.3 Application of PPBL Strategy in Graduation Design Studio -- 4 Methodology -- 4.1 Course Overview and Learning Method -- 4.2 Participants -- 4.3 Course Grades Evaluation -- 4.4 Statistical Analysis -- 5 Results and Discussion -- 5.1 General Information -- 5.2 Technical Preferences for Blended Learning -- 5.3 Course Outcome Survey -- 5.4 Advantages and Disadvantages of PPBL -- 5.5 Students' Performance -- 6 Conclusion -- References -- An Efficient 2-Stages Classification Model for Students Performance Prediction -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Dataset -- 5 Classifiers -- 6 Experimental Results and Discussion -- 7 Environment -- 8 Evaluation Measures -- 9 Results and Discussion -- 10 Conclusion and Future Work -- References -- A Straggler Identification Model for Large-Scale Distributed Computing Systems Using Machine Learning -- 1 Introduction -- 2 The Proposed Model for Straggler Identification Using Machine Learning -- 2.1 Parameter Selection -- 2.2 Model Training -- 2.3 Machine Learning Models -- 3 Simulation Results and Discussion -- 3.1 Benchmarks -- 3.2 Performance Evaluation -- 4 Conclusion -- References -- The Application of Artificial Intelligence in Real Estate Valuation: A Systematic Review -- 1 Introduction -- 2 Research Objectives -- 3 Literature Review -- 4 Big Data, Artificial Intelligence, and Machine Learning in Real Estate Valuation -- 5 Research Methodology -- 6 Research Questions -- 7 Inclusion/Exclusion Criteria -- 8 Data Sources and Search Strategies -- 9 Quality Assessment -- 10 Study Results and Discussion: -- 11 Conclusion -- 12 Limitations and Further Studies -- References -- Agency Theory: Designing Optimal Incentives in the Insurance Sector -- 1 Introduction. 2 Principal-Agent Contract Definition at an Insurance Company -- 2.1 Main Concepts Definition -- 2.2 Removing the Stochastic Nature of the Contract Types -- 2.3 Estimating the Agent's Effort Function -- 2.4 Properties and Method Proposed -- 3 Practical Case -- 4 Conclusions -- References -- Deep Learning and Applications -- Face Mask Detection by Using Deep Learning with the Generative Adversarial Network-Based Feature -- 1 Introduction -- 2 Related Works -- 3 The Proposed Method -- 3.1 The Proposed GAN Model for Extracing Robust Learning Features -- 3.2 The Proposed Face Mask Detection and Classification by Using YOLOv5 -- 4 Experimental Results -- 5 Conclusion -- References -- Face Recognition Based on Deep Learning and HSV Color Space -- 1 Introduction -- 2 Related Work -- 3 The Proposed Method -- 4 Experimental Results -- 5 Conclusion -- References -- A Proposed Model for Fake Media Detection Using Deep Learning Techniques -- 1 Introduction -- 2 Related Work -- 3 Exposed Deepfake Videos -- 3.1 Creating Deepfake -- 3.2 Training -- 3.3 Video Generation -- 4 Methodology -- 5 Experiments -- 5.1 Datasets -- 5.2 Results -- 5.3 Metrics for Evaluation -- 6 Conclusions and Future Research Directions -- References -- A Comparison of Deep Learning Techniques for Corrosion Detection -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Deep Learning -- 3.2 Transfer Learning -- 4 Methodology -- 4.1 Dataset Preparation -- 4.2 Evaluation Metrics -- 4.3 Training the Models -- 5 Results and Discussion -- 5.1 Results -- 5.2 Discussion -- 5.3 Conclusion -- References -- Pleural Effusion Detection Using Machine Learning and Deep Learning Based on Computer Vision -- 1 Introduction -- 2 Problem Formulation -- 3 System Model -- 3.1 Dataset Collection -- 3.2 Model (1): Pleural Effusion Detection Using Machine Learning. 3.3 Model (2): Pleural Effusion Detection Using Deep Learning Algorithms -- 4 Simulation Result and Discussion -- 4.1 Result of Model (1) Pleural Effusion Detection Using Machine Learning -- 4.2 Result of Model (2) Pleural Effusion Detection Using Deep Learning -- 5 Conclusion -- References -- Explainable Artificial Intelligence Powered Model for Explainable Detection of Stroke Disease -- 1 Introduction -- 2 Background -- 3 Literature Review -- 4 Dataset and Proposed Model Techniques -- 4.1 Data Acquisition -- 4.2 Data Preprocessing -- 4.3 Proposed Model -- 5 Results and Discussion -- 5.1 Predicated Result -- 5.2 Global Explanation -- 5.3 Local Explanation -- 6 Conclusion and Future Work -- References -- Research on Two-Wheeled Vehicle Entry Ban System Based on Deep Learning -- 1 Introduction -- 2 Overall System Scheme -- 2.1 Hardware Components -- 2.2 System Flow Chart -- 3 Acquisition of Video Images -- 3.1 Video Image Pre-processin -- 3.2 Motion Object Extraction -- 4 Elevator Entry Prohibition System -- 4.1 Selection of Detection and Recognition Algorithms -- 4.2 Forbidden to Enter the System Feedback Brake Part -- 5 Experimental Results and Analysis -- 5.1 Collection of Datasets -- 5.2 Comparative Results -- 6 Conclusion -- References -- Detection of Coronavirus (COVID-19) Associated Pneumonia Based on Generative Adversarial Networks and a Fine-Tuned Deep Transfer Learning Model Using Chest X-ray Dataset -- 1 Introduction -- 2 Related Works -- 3 Generative Adversarial Networks and Deep Transfer Learning -- 3.1 GAN Architecture -- 3.2 Deep Transfer Learning Networks -- 4 Datasets Characteristics -- 5 Proposed Model -- 5.1 The Augmentation Process Using Generative Adversarial Networks (GAN) -- 6 Experimental Results -- 6.1 Confusion Matrix and Testing Accuracy -- 6.2 Performance Evaluation -- 7 Conclusions and Future Works -- References. Alzheimer's Disease Multi-class Classification Model Based on CNN and StackNet Using Brain MRI Data. |
| Record Nr. | UNINA-9910631088703321 |
| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2016 [[electronic resource] /] / edited by Aboul Ella Hassanien, Khaled Shaalan, Tarek Gaber, Ahmad Taher Azar, M. F. Tolba
| Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2016 [[electronic resource] /] / edited by Aboul Ella Hassanien, Khaled Shaalan, Tarek Gaber, Ahmad Taher Azar, M. F. Tolba |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XXVII, 913 p. 326 illus.) |
| Disciplina | 006.33 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Artificial intelligence Computational Intelligence Artificial Intelligence |
| ISBN | 3-319-48308-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Further Investigations for Documents Information Retrieval Based on Discrete Wavelet Transform -- Knowledge Representation in Intelligent Tutoring System -- A new method for interoperability between lexical resources using MDA approach -- Optimizing Fuzzy Inference Systems for Improving Speech Emotion Recognition -- Arabic fine-grained opinion categorization using discriminative machine learning technique -- A Spell Correction Model for OCR Errors for Arabic Text -- Natural Language Processing for Arabic Metaphors: A Conceptual Approach -- Using Text Mining To Analyze Real Estate Classifieds. |
| Record Nr. | UNINA-9910136001503321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2017 [[electronic resource] /] / edited by Aboul Ella Hassanien, Khaled Shaalan, Tarek Gaber, Mohamed F. Tolba
| Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2017 [[electronic resource] /] / edited by Aboul Ella Hassanien, Khaled Shaalan, Tarek Gaber, Mohamed F. Tolba |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XX, 917 p. 433 illus.) |
| Disciplina | 006.3 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Artificial intelligence Computational Intelligence Artificial Intelligence |
| ISBN | 3-319-64861-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910299885003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018 [[electronic resource] /] / edited by Aboul Ella Hassanien, Mohamed F. Tolba, Khaled Shaalan, Ahmad Taher Azar
| Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018 [[electronic resource] /] / edited by Aboul Ella Hassanien, Mohamed F. Tolba, Khaled Shaalan, Ahmad Taher Azar |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (683 pages) |
| Disciplina | 006.3 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Artificial intelligence Computational Intelligence Artificial Intelligence |
| ISBN | 3-319-99010-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910483848803321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2019 [[electronic resource] /] / edited by Aboul Ella Hassanien, Khaled Shaalan, Mohamed Fahmy Tolba
| Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2019 [[electronic resource] /] / edited by Aboul Ella Hassanien, Khaled Shaalan, Mohamed Fahmy Tolba |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XXII, 1090 p. 506 illus., 327 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Artificial intelligence Computational Intelligence Artificial Intelligence |
| ISBN | 3-030-31129-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910484228203321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2020 / / Aboul Ella Hassanien [and four others] editors
| Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2020 / / Aboul Ella Hassanien [and four others] editors |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XVIII, 893 p. 437 illus., 308 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico | Artificial intelligence |
| ISBN | 3-030-58669-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910483328103321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of the international conference on advanced intelligent systems and informatics 2021 / / Aboul Ella Hassanien [and four others] editors
| Proceedings of the international conference on advanced intelligent systems and informatics 2021 / / Aboul Ella Hassanien [and four others] editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (412 pages) |
| Disciplina | 006.3 |
| Collana | Lecture Notes on Data Engineering and Communications Technologies |
| Soggetto topico | Artificial intelligence |
| ISBN | 3-030-89701-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910523759903321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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