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Deep learning for unmanned systems / / Anis Koubaa, Ahmad Taher Azar, editors
| Deep learning for unmanned systems / / Anis Koubaa, Ahmad Taher Azar, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (731 pages) |
| Disciplina | 006.31 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Automated vehicles - Control
Automated vehicles - Data processing Machine learning Vehicles Aprenentatge automàtic |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-77939-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910502972903321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Deep learning in computational mechanics : an introductory course / / Stefan Kollmannsberger [and three others]
| Deep learning in computational mechanics : an introductory course / / Stefan Kollmannsberger [and three others] |
| Autore | Kollmannsberger Stefan |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (108 pages) |
| Disciplina | 006.31 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Machine learning
Neural networks (Computer science) Neural Networks, Computer Aprenentatge automàtic Xarxes neuronals (Informàtica) |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-76587-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910495351203321 |
Kollmannsberger Stefan
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| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Deep learning in multi-step prediction of chaotic dynamics : from deterministic models to real-world systems / / Matteo Sangiorgio, Fabio Dercole, Giorgio Guariso
| Deep learning in multi-step prediction of chaotic dynamics : from deterministic models to real-world systems / / Matteo Sangiorgio, Fabio Dercole, Giorgio Guariso |
| Autore | Sangiorgio Matteo |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (111 pages) |
| Disciplina | 003.857015118 |
| Collana | SpringerBriefs in Applied Sciences and Technology |
| Soggetto topico |
Caos (Teoria de sistemes)
Models matemàtics Aprenentatge automàtic Chaotic behavior in systems - Mathematical models Deep learning (Machine learning) |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-94482-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910544860003321 |
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Sangiorgio Matteo
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| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Deep learning in multi-step prediction of chaotic dynamics : from deterministic models to real-world systems / / Matteo Sangiorgio, Fabio Dercole, Giorgio Guariso
| Deep learning in multi-step prediction of chaotic dynamics : from deterministic models to real-world systems / / Matteo Sangiorgio, Fabio Dercole, Giorgio Guariso |
| Autore | Sangiorgio Matteo |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (111 pages) |
| Disciplina | 003.857015118 |
| Collana | SpringerBriefs in Applied Sciences and Technology |
| Soggetto topico |
Caos (Teoria de sistemes)
Models matemàtics Aprenentatge automàtic Chaotic behavior in systems - Mathematical models Deep learning (Machine learning) |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-94482-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996466549203316 |
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Sangiorgio Matteo
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| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Development and future of internet of drones (IoD) : insights, trends and road ahead / / Rajalakshmi Krishnamurthi, Anand Nayyar, Aboul Ella Hassanien, editors
| Development and future of internet of drones (IoD) : insights, trends and road ahead / / Rajalakshmi Krishnamurthi, Anand Nayyar, Aboul Ella Hassanien, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (275 pages) |
| Disciplina | 004.678 |
| Collana | Studies in Systems, Decision and Control |
| Soggetto topico |
Internet of things
Drone aircraft - Automatic control Aerial surveillance - Automatic control Drons Internet de les coses Aprenentatge automàtic Intel·ligència artificial |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-63339-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910483663903321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Embedded machine learning for cyber-physical, IoT, and edge computing : hardware architectures / / Sudeep Pasricha, Muhammad Shafique, editors
| Embedded machine learning for cyber-physical, IoT, and edge computing : hardware architectures / / Sudeep Pasricha, Muhammad Shafique, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2024] |
| Descrizione fisica | 1 online resource (418 pages) |
| Disciplina | 006.22 |
| Soggetto topico |
Embedded computer systems
Cooperating objects (Computer systems) Artificial intelligence Embedded Systems Cyber-Physical Systems Artificial Intelligence Sistemes incrustats (Informàtica) Objectes cooperants (Sistemes informàtics) Informàtica a la perifèria Aprenentatge automàtic |
| ISBN |
9783031195686
3-031-19568-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Efficient Hardware Acceleration for Embedded Machine Learning -- Memory Design and Optimization for Embedded Machine Learning -- Efficient Software Design of Embedded Machine Learning -- Hardware-Software Co-Design for Embedded Machine Learning -- Emerging Technologies for Embedded Machine Learning -- Mobile, IoT, and Edge Application Use-Cases for Embedded Machine Learning -- Cyber-Physical Application Use-Cases for Embedded Machine Learning. |
| Record Nr. | UNINA-9910760273503321 |
| Cham, Switzerland : , : Springer, , [2024] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Enabling machine learning applications in data science : proceedings of Arab Conference for Emerging Technologies 2020 / / Aboul Ella Hassanien [and three others] editors
| Enabling machine learning applications in data science : proceedings of Arab Conference for Emerging Technologies 2020 / / Aboul Ella Hassanien [and three others] editors |
| Pubbl/distr/stampa | Gateway East, Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (392 pages) |
| Disciplina | 006.31 |
| Collana | Algorithms for Intelligent Systems |
| Soggetto topico |
Machine learning
Aprenentatge automàtic Intel·ligència artificial |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 981-336-129-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- About the Editors -- Part I Machine Learning and Intelligent Systems Applications -- 1 Who Is Typing? Automatic Gender Recognition from Interactive Textual Chats Using Typing Behaviour -- 1 Introduction -- 2 Background and Related Work -- 3 The Data -- 4 The Approach -- 4.1 Feature Extraction -- 4.2 Classification -- 5 Results and Discussion -- 5.1 Classification Results -- 5.2 Identification of Gender Makers -- 6 Conclusion -- References -- 2 An Efficient Framework to Build Up Heart Sounds and Murmurs Datasets Used for Automatic Cardiovascular Diseases Classifications -- 1 Introduction -- 2 Related Work -- 3 Proposed Framework -- 3.1 Dataset Logical Structure -- 3.2 Mobile Application and Database Design -- 3.3 Composition Stethoscope -- 4 Conclusion -- References -- 3 Facial Recognition and Emotional Expressions Over Video Conferencing Based on Web Real Time Communication and Artificial Intelligence -- 1 Introduction -- 2 WebRTC -- 2.1 WebRTC Client-Side -- 2.2 WebRTC Server-Side -- 3 Machine Learning -- 3.1 Machine Learning Models Examples -- 3.2 Machine Learning Libraries Examples -- 4 Implementation -- 4.1 Network Topology -- 4.2 Deployment -- 4.3 Results and Observations -- 5 Conclusion and Future Work -- References -- 4 Recent Advances in Intelligent Imaging Systems for Early Prediction of Colorectal Cancer: A Perspective -- 1 Introduction -- 2 Epidemiology of Colorectal Cancer -- 2.1 Current Trends in Incidence and Mortality of Colorectal Cancer -- 2.2 Etiology of Colorectal Cancer -- 3 Medical Diagnostic Procedures for Screening of Colorectal Cancer -- 4 Necessity for Early Prediction of Colorectal Cancer -- 5 Challenges in Early Detection of Colorectal Cancer -- 6 Analysis of Intelligent Medical Imaging Techniques for Early Detection of Colorectal Cancer -- 6.1 Collection of CRC Frames.
6.2 Preprocessing -- 6.3 Intelligent Training Engine for Polyp Detection -- 6.4 Performance Evaluation -- 7 Discussion and Future Directions -- 8 Conclusion -- References -- 5 Optimal Path Schemes of Mobile Anchor Nodes Aided Localization for Different Applications in IoT -- 1 Introduction -- 2 Mobility Based Localization Model in WSN -- 3 Static Unknown Nodes, Mobile Anchor Nodes Class -- 3.1 Mobile Anchor Paths -- 4 Comparative Analysis -- 5 Conclusions -- References -- 6 Artificial Intelligence in 3D Printing -- 1 Introduction -- 2 Background and Basic Concepts -- 2.1 Additive Manufacturing (AM) -- 2.2 Artificial Intelligence (AI) -- 2.3 Machine Learning (ML) -- 3 Artificial Intelligence Applications in 3D Printing -- 3.1 Original Printability Checker -- 3.2 Improvement by ML -- 3.3 Further Developments -- 3.4 Slicing Acceleration -- 3.5 Path Optimization -- 3.6 Further Developments -- 3.7 Service Platform and Evaluation -- 3.8 Cloud Service Platform -- 3.9 Service Evaluation -- 3.10 Further Developments -- 3.11 Attack Detection -- 3.12 Further Developments -- 4 Conclusion -- References -- 7 Finding Suitable Threshold for Support in Apriori Algorithm Using Statistical Measures -- 1 Introduction -- 2 Background of Association Rules Mining -- 2.1 Process Association Rules Mining -- 2.2 Statistical Measures -- 3 Proposed Approach -- 4 Experiment Study -- 4.1 Reduction of a Number of Rules -- 4.2 The Running Time Analysis -- 4.3 The Quality of the Extracted Rules -- 5 Conclusion -- References -- 8 Optimum Voltage Sag Compensation Strategies Using DVR Series with the Critical Loads -- 1 Introduction -- 2 DVR Operation Characteristics -- 3 Tests and Results -- 3.1 Load Side Voltage Sag Protection -- 3.2 Load Side Voltage Swell Protection -- 4 Conclusion -- References -- 9 Robust Clustering Based Possibilistic Type-2 Fuzzy C-means for Noisy Datasets. 1 Introduction -- 2 Materials and Methods -- 2.1 A Brief Review of the Baseline Methods -- 2.2 Discussion -- 3 Improved Possibilistic Type-2 Fuzzy C-means Clustering-Based Cluster Forests (IP-T2-FCM-CF) -- 4 Evaluation of the Proposed IP-T2-FCM-CF Algorithm -- 4.1 Experiments Setup -- 4.2 Experimental Results -- 4.3 Results' Discussion -- 5 Conclusion -- References -- 10 Wind Distributed Generation with the Power Distribution Network for Power Quality Control -- 1 Introduction -- 2 DG Installation Based on Voltage Stability -- 2.1 Analyzing of Active and Reactive Power Flow -- 3 Wind Energy Conversion with the Power System -- 3.1 Output Power and Compensation of Wind Generation -- 3.2 Wind Generation Control -- 4 Simulation and Discussion -- 5 Conclusion -- References -- 11 Implementation of Hybrid Algorithm for the UAV Images Preprocessing Based on Embedded Heterogeneous System: The Case of Precision Agriculture -- 1 Introduction -- 2 Precision Agriculture: Application and Algorithms -- 3 Image Processing in Precision Agriculture -- 3.1 Challenge and Proposed Method -- 4 Deblurring Algorithms -- 4.1 Blind Approach -- 4.2 Non-blind Approach -- 4.3 Deblurring Algorithms -- 5 Proposed Work -- 6 Results and Discussion -- 7 Conclusion and Perspectives -- References -- 12 SLAM Algorithm: Overview and Evaluation in a Heterogeneous System -- 1 Introduction -- 2 SLAM: Overview and Approach -- 3 Evaluation and Result -- 4 Conclusion -- References -- 13 Implementing big OLAP Cubes using a NoSQL-Based approach: Cube models and aggregation operators -- 1 Introduction -- 2 State of the Art -- 3 Contribution -- 3.1 Background -- 3.2 Approach Overview -- 3.3 First Approach -- 3.4 Second Approach -- 4 Implementation -- 4.1 Experiments Setting -- 4.2 Result and Evaluation -- 5 Conclusion -- References. 14 Multi-objective Quantum Moth Flame Optimization for Clustering -- 1 Introduction -- 2 The Quantum-Behaved MFO (Q-MFO) -- 2.1 Moth Flame Optimization (MFO) -- 2.2 Quantum-Behaved MFO (QMFO) -- 3 Multi-Objective QMFO (MOQMFO) -- 4 MOQMFO for Clustering -- 5 MOQMFO Flowchart -- 6 Experiments -- 6.1 Datasets -- 6.2 Scenario -- 6.3 Results and Discussion -- 7 Conclusion and Perspectives -- References -- 15 On Optimizing the Visual Quality of HASM-Based Streaming-The Study the Sensitivity of Motion Estimation Techniques for Mesh-Based Codecs in Ultra High Definition Large Format Real-Time Video Coding -- 1 Introduction -- 2 Literature Review -- 3 Mesh Generation Techniques -- 3.1 Ordinal Three Step Search -- 3.2 Leap Three Step Search -- 3.3 Grid Three Step Search -- 3.4 Diamond Three Step Search -- 4 Experimental Results and Discussion -- 4.1 Video Sequences -- 4.2 Experimental Results -- 4.3 Discussion -- 5 Conclusion -- References -- 16 Rough Sets Crow Search Algorithm for Inverse Kinematics -- 1 Introduction -- 2 Rough Crow Search Algorithm for Inverse Kinematics -- 2.1 The Crow Search Algorithm -- 2.2 The Rough Searching Scheme -- 2.3 The Rough Crow Search Algorithm -- 3 The Forward Kinematics Model of Kuka-Kr16 -- 4 Experimental Analysis -- 4.1 Comparative Results -- 4.2 Non-parametric Statistical Analyses -- 5 Discussion and Perspectives -- References -- 17 Machine Learning for Predicting Cancer Disease: Comparative Analysis -- 1 Introduction -- 2 Background -- 3 Machine Learning: Review of Literature -- 3.1 Artificial Neural Network (ANN) -- 3.2 Support Vector Machine (SVM) -- 3.3 K-Nearest Neighbor Algorithm (KNN) -- 4 Discussion and Analysis -- 5 Conclusion and Future Works -- References -- 18 Modeling and Performance Evaluation of LoRa Network Based on Capture Effect -- 1 Introduction -- 2 Related Work -- 3 LoRa Overview. 3.1 LoRa Physical Layer -- 3.2 LoRaWAN -- 3.3 LoRa Network Architecture -- 4 Model Scenario and Problem Statement -- 5 Markov Model -- 5.1 Performance Parameters for Unbacklogged Packets -- 5.2 Performance Parameters for Backlogged Packets -- 5.3 Finding the Social Optimum -- 6 Numerical Results -- 7 Conclusion and Perspectives -- References -- Part II Deep Learning Applications -- 19 ESwish Beta: Modifying Swish Activation Function for Deep Learning Improvement -- 1 Introduction -- 2 Related Works -- 3 ESwish Beta -- 4 Experiments and Results -- 4.1 MNIST Dataset -- 4.2 CIFAR 10 Dataset -- 4.3 CIFAR 100 Dataset -- 5 Conclusion -- References -- 20 Online Arabic Handwriting Recognition Using Graphemes Segmentation and Deep Learning Recurrent Neural Networks -- 1 Introduction -- 2 Arabic Script Specificity -- 3 Related Work -- 4 System Overview -- 4.1 Preprocessing -- 4.2 Baseline Detection and Grapheme Segmentation -- 4.3 Feature Extraction -- 4.4 Sequence Recognition -- 5 Experimental Results -- 5.1 Dataset -- 5.2 Results and Discussion -- 5.3 Comparison with the State of the Art -- 6 Conclusion -- References -- 21 On the Application of Real-Time Deep Neural Network for Automatic License Plate Reading from Sequence of Images Targeting Edge Artificial Intelligence Architectures -- 1 Introduction -- 2 Data Collection and Annotation -- 2.1 Annotation Types -- 2.2 Annotation Formats -- 2.3 Annotation Tool -- 3 Traning Models -- 3.1 Single-Shot Detector (SSD) -- 3.2 Faster Region-Based Convolution Neural Networks (Faster R-CNN) -- 3.3 Yolo -- 4 Optimization Hyperparameters -- 4.1 Learning Rate -- 4.2 Batch Size -- 4.3 Epochs -- 5 Experimental Setup -- 6 Results and Discussions -- 7 Conclusion and Future Work -- References -- 22 Localization of Facial Images Manipulation in Digital Forensics via Convolutional Neural Networks -- 1 Introduction. 2 Related Work. |
| Record Nr. | UNINA-9910484221903321 |
| Gateway East, Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Explainable neural networks based on fuzzy logic and multi-criteria decision tools / / József Dombi, Orsolya Csiszár
| Explainable neural networks based on fuzzy logic and multi-criteria decision tools / / József Dombi, Orsolya Csiszár |
| Autore | Dombi József |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (186 pages) |
| Disciplina | 006.32 |
| Collana | Studies in fuzziness and soft computing |
| Soggetto topico |
Fuzzy logic
Neural networks (Computer science) Machine learning Artificial intelligence Xarxes neuronals (Informàtica) Lògica difusa Aprenentatge automàtic |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-72280-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Foreword -- Preface -- Introduction-Aggregation and Intelligent Decision -- Contents -- List of Figures -- List of Tables -- Elements of Nilpotent Fuzzy Logic -- 1 Connectives: Conjunctions, Disjunctions and Negations -- 1.1 Introduction -- 1.2 Preliminaries -- 1.2.1 Negations -- 1.2.2 Triangular Norms and Conorms -- 1.3 Characterization of Strict Negation Operators -- 1.4 Nilpotent Connective Systems -- 1.4.1 Structural Properties of Connective Systems -- 1.4.2 Consistent Connective Systems -- 1.5 Summary -- References -- 2 Implications -- 2.1 Introduction -- 2.2 Preliminaries -- 2.3 R-Implications in Bounded Systems -- 2.4 S-Implications in Bounded Systems -- 2.4.1 Properties of iSn, iSd and iSc -- 2.4.2 S-Implications and the Ordering Property -- 2.5 A Comparison of Implications in Bounded Systems -- 2.6 Min and Max Operators in Nilpotent Connective Systems -- 2.7 Summary -- References -- 3 Equivalences -- 3.1 Introduction -- 3.2 Preliminaries -- 3.3 Equivalences in Bounded Systems -- 3.3.1 Properties of ec(x,y) and ed(x,y) -- 3.4 Dual Equivalences -- 3.4.1 Properties of bared and barec -- 3.5 Arithmetic Mean Operators in Bounded Systems -- 3.6 Aggregated Equivalences -- 3.6.1 Properties of the Aggregated Equivalence Operator -- 3.7 Applications -- 3.8 Summary -- References -- 4 Modifiers and Membership Functions in Fuzzy Sets -- 4.1 Introduction -- 4.2 Unary Operators in Nilpotent Logical Systems -- 4.2.1 Possibility and Necessity as Unary Operators Derived from Multivariable Operators -- 4.2.2 Drastic Unary Operators -- 4.2.3 Composition Rules -- 4.2.4 Multivariable Operators Derived from Unary Operators -- 4.2.5 A General Framework: The α, β, γ- Model -- 4.3 Unary Operators Induced by Negation Operators -- 4.4 Membership Functions -- 4.5 Non-membership Functions -- 4.6 Summary -- References -- Decision Operators.
5 Aggregative Operators -- 5.1 Introduction -- 5.2 Preliminaries -- 5.3 Shifting Transformations on the Generator Functions - A General Parametric Formula -- 5.4 The Weighted General Operator -- 5.5 Properties of the General and the Weighted General Operator -- 5.5.1 The De Morgan Property -- 5.5.2 Bisymmetry -- 5.6 The Two-Variable General and Weighted Aggregative Operator -- 5.7 Summary -- References -- 6 Preference Operators -- 6.1 Introduction -- 6.2 Operators of Nilpotent Systems - A General Framework -- 6.2.1 Normalization of the Generator Functions -- 6.2.2 The General Parametric Operator -- 6.2.3 The Unary Operators: Negation, Modifiers and Hedges -- 6.3 Preference Modeling -- 6.4 Properties of the Preference Operator -- 6.4.1 Basic Properties -- 6.4.2 Ordering Properties -- 6.4.3 Preference and Negation -- 6.4.4 Preference, Conjunction and Disjunction -- 6.4.5 Preference and Aggregation -- 6.4.6 Additive Transitivity -- 6.4.7 Bisymmetry and the Common Base Property -- 6.4.8 Preference and Unary Operators -- 6.5 Summary -- References -- Learning and Neural Networks -- 7 Squashing Functions -- 7.1 Introduction -- 7.2 Łukasiewicz Operators -- 7.3 Approximation of the Cutting Function -- 7.3.1 The Sigmoid Function -- 7.3.2 The Interval [a,b] Squashing Function -- 7.3.3 The Error of the Approximation -- 7.4 Approximation of Piecewise Linear Membership Functions -- 7.5 Summary -- References -- 8 Learning Rules -- 8.1 Introduction -- 8.2 Problem Definition and Solution Outline -- 8.3 Preliminaries -- 8.4 The Structure and Representation of the Rules -- 8.5 The Optimization Process -- 8.5.1 Rule Optimization by GA -- 8.5.2 A Gradient-Based Local Optimization of Memberships -- 8.6 Applications -- 8.7 Summary -- References -- 9 Interpretable Neural Networks Based on Continuous-Valued Logic and Multi-criteria Decision Operators -- 9.1 Introduction. 9.2 Related Work -- 9.3 Nilpotent Logical Systems and Multicriteria Decision Tools -- 9.4 Nilpotent Logic-Based Interpretation of Neural Networks -- 9.5 Playground Examples -- 9.5.1 XOR -- 9.5.2 Preference -- 9.6 Summary -- References -- 10 Conclusions. |
| Record Nr. | UNINA-9910482999203321 |
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Dombi József
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| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Federated learning systems : towards next-generation AI / / Muhammad Habib ur Rehman, Mohamed Medhat Gaber, editors
| Federated learning systems : towards next-generation AI / / Muhammad Habib ur Rehman, Mohamed Medhat Gaber, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (207 pages) |
| Disciplina | 006.31 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Machine learning
Computational intelligence Aprenentatge automàtic Intel·ligència computacional |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-70604-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910484494903321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Geometry of deep learning : a signal processing perspective / / Jong Chul Ye
| Geometry of deep learning : a signal processing perspective / / Jong Chul Ye |
| Autore | Ye Jong Chul |
| Pubbl/distr/stampa | Gateway East, Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (338 pages) |
| Disciplina | 006.31 |
| Collana | Mathematics in industry |
| Soggetto topico |
Deep learning (Machine learning)
Geometry Neural networks (Computer science) Aprenentatge automàtic Xarxes neuronals (Informàtica) Geometria |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
981-16-6045-X
981-16-6046-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910743375203321 |
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Ye Jong Chul
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| Gateway East, Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Soggetto topico
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Aprenentatge automàtic
(101)
- Machine learning (64)
- Machine Learning (17)
- Processament de dades (17)
- Intel·ligència artificial (15)