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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy [[electronic resource] ] : SPIoT-2020, Volume 1 / / edited by John MacIntyre, Jinghua Zhao, Xiaomeng Ma
| The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy [[electronic resource] ] : SPIoT-2020, Volume 1 / / edited by John MacIntyre, Jinghua Zhao, Xiaomeng Ma |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (XXXI, 884 p. 221 illus., 150 illus. in color.) |
| Disciplina | 620.00285 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Engineering—Data processing
Cooperating objects (Computer systems) Computational intelligence Machine learning Big data Data Engineering Cyber-Physical Systems Computational Intelligence Machine Learning Big Data |
| ISBN | 3-030-62743-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910483068103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy [[electronic resource] ] : SPIoT-2020, Volume 2 / / edited by John MacIntyre, Jinghua Zhao, Xiaomeng Ma
| The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy [[electronic resource] ] : SPIoT-2020, Volume 2 / / edited by John MacIntyre, Jinghua Zhao, Xiaomeng Ma |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (XXXII, 863 p. 222 illus., 128 illus. in color.) |
| Disciplina | 004.678 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Engineering—Data processing
Cooperating objects (Computer systems) Computational intelligence Machine learning Big data Data Engineering Cyber-Physical Systems Computational Intelligence Machine Learning Big Data |
| ISBN | 3-030-62746-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910483082303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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The 8th International Conference on Advanced Machine Learning and Technologies and Applications (AMLTA2022) [[electronic resource] /] / edited by Aboul Ella Hassanien, Rawya Y. Rizk, Václav Snášel, Rehab F. Abdel-Kader
| The 8th International Conference on Advanced Machine Learning and Technologies and Applications (AMLTA2022) [[electronic resource] /] / edited by Aboul Ella Hassanien, Rawya Y. Rizk, Václav Snášel, Rehab F. Abdel-Kader |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (708 pages) |
| Disciplina | 006.3 |
| Collana | Lecture Notes on Data Engineering and Communications Technologies |
| Soggetto topico |
Computational intelligence
Artificial intelligence Big data Engineering - Data processing Computational Intelligence Artificial Intelligence Big Data Data Engineering |
| ISBN | 3-031-03918-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Honorary Chair -- General Chairs -- Co-chairs -- International Advisory Board -- Publication Chair -- Program Chairs -- Publicity Chairs -- Technical Program Committee -- Local Arrangement Chairs -- Contents -- Deep Learning and Applications -- Plant Leaf Diseases Detection and Identification Using Deep Learning Model -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 4 Experimental Results -- 5 Conclusions -- References -- Reinforcement Learning for Developing an Intelligent Warehouse Environment -- 1 Introduction -- 2 Machine Learning Techniques -- 3 Results and Discussion -- 4 Conclusion and Future Research -- References -- A Low-Cost Multi-sensor Deep Learning System for Pavement Distress Detection and Severity Classification -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Overall System Architecture -- 3.2 Deep Learning Distress Detection -- 3.3 Dataset and Training Information -- 3.4 Projection onto the Depth 3D Point Cloud and ROI Filtering -- 4 Case Study: Pothole Severity Classification -- 5 Experimental Results -- 5.1 Results for the Distress Detection -- 5.2 Results for Pothole Severity Classification -- 6 Conclusion -- References -- An Intrusion Detection Model Based on Deep Learning and Multi-layer Perceptron in the Internet of Things (IoT) Network -- 1 Introduction -- 2 Related Work -- 2.1 Multi Agent Systems for IDS -- 2.2 Fuzzy Systems for IDS -- 2.3 Game Theory Models for IDS -- 3 Architecture of the Proposed Intrusion Detection System -- 3.1 Pre-processing and Feature Engineering -- 3.2 Deep Learning Layer -- 3.3 Evaluation Layer -- 4 The Experimental Results -- 5 Comparison Between Proposed Models and the Others -- 6 Conclusion -- References -- Transfer Learning and Recurrent Neural Networks for Automatic Arabic Sign Language Recognition -- 1 Introduction.
2 Related Work -- 3 Arabic Sign Language Dataset -- 4 Methodology -- 4.1 Prepare the Dataset -- 4.2 Extract the Spatial Features -- 4.3 Extract the Temporal Features -- 4.4 Video Augmentation -- 5 Experimental and Results -- 5.1 Experiment Settings -- 5.2 Models Results -- 6 Conclusion and Future Works -- References -- Robust Face Mask Detection Using Local Binary Pattern and Deep Learning -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 4 Experimental Results -- 5 Conclusion -- References -- Steganography Adaptation Model for Data Security Enhancement in Ad-Hoc Cloud Based V-BOINC Through Deep Learning -- 1 Introduction -- 1.1 Ad-Hoc Cloud Computing -- 1.2 Deep Steganography -- 1.3 Contribution -- 1.4 Paper Organization -- 2 Literature Review -- 3 Proposed Solution -- 4 Experiment -- 5 Discussion and Analysis -- 6 Conclusion -- References -- Performance of Different Deep Learning Models for COVID-19 Detection -- 1 Introduction -- 2 Deep Learning (DL) -- 2.1 The DL-Algorithms Steps in COVID-19 Diagnosis -- 2.2 DL-Models for COVID-19 Detection -- 3 Discussion -- 4 Conclusion -- References -- Deep Learning-Based Apple Leaves Disease Identification Approach with Imbalanced Data -- 1 Introduction -- 2 Basics and Background -- 2.1 Data Imbalance -- 2.2 Convolutional Neural Networks -- 2.3 Transfer Learning -- 3 The Proposed Approach -- 3.1 Dataset Description -- 3.2 Data Preprocessing Phase -- 3.3 Training Phase -- 3.4 Evaluation Phase -- 4 Experimental Results and Analysis -- 4.1 Data Imbalance Problem -- 4.2 Data Augmentation -- 4.3 Setup of the Experiment -- 4.4 Evaluation of the Model -- 5 Conclusion and Future Work -- References -- Commodity Image Retrieval Based on Image and Text Data -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Image and Text Feature Fusion -- 3.2 Target Function -- 4 Experiment -- 4.1 Evaluation Metrics. 4.2 Datasets -- 4.3 Experimental Details -- 4.4 Experimental Results and Analysis -- 5 Conclusion -- References -- Machine Learning Technologies -- Artificial Intelligence Based Solutions to Smart Warehouse Development: A Conceptual Framework -- 1 Introduction -- 2 SWOT Analysis -- 2.1 Strengths -- 2.2 Weaknesses -- 2.3 Opportunities -- 2.4 Threats -- 3 Proposed Solutions and Current Approaches -- 3.1 WO Strategy (Improve): Testbed as a Trial for Investment Decision -- 3.2 WO Strategy (Improve): AI-Powered Solutions -- 3.3 SO Strategy (Attack): AI Resource Development -- 4 Conclusions and Future Research -- References -- Long-Short Term Memory Model with Univariate Input for Forecasting Individual Household Electricity Consumption -- 1 Introduction -- 2 Related Works -- 3 Deep Learning Models for Load Forecasting -- 3.1 LSTM and LSTM-ED Neural Networks -- 3.2 CNN-LSTM Neural Networks -- 3.3 GRU Neural Networks -- 3.4 BiLSTM Neural Networks -- 3.5 ConvLSTM Neural Networks -- 4 Results and Discussion -- 4.1 Dataset Description -- 4.2 Evaluation Metrics -- 4.3 Prediction Results of ConvLSTM -- 4.4 Discussion of the Forecasting Models -- 5 Conclusion and Future Work -- References -- DNA-Binding-Proteins Identification Based on Hybrid Features Extraction from Hidden Markov Model -- 1 Introduction -- 2 Materials and Methods -- 2.1 Datasets -- 2.2 Encoding -- 2.3 Framing -- 2.4 Hybrid Visual HMM Structure -- 2.5 Features Extraction -- 2.6 Classifier -- 3 Results and Discussions -- 4 Conclusions -- References -- Machine Learning Based Mobile Applications for Cardiovascular Diseases (CVDs) -- 1 Introduction -- 2 ML Based m-Health for CVDs -- 3 Characteristics of the Commercially Available CVDs Mobile Applications -- 4 Future Requirements -- 5 Conclusion -- References -- Regression Analysis for Remaining Useful Life Prediction of Aircraft Engines. 1 Introduction -- 2 Related Work -- 3 Aircraft Engine System -- 4 Proposed Model for Predicting the RUL -- 5 Experimental Results and Discussion -- 6 Conclusion and Future Work -- References -- Applying Machine Learning Technology to Perform Automatic Provisioning of the Optical Transport Network -- 1 Introduction -- 2 The Challenges in the Current Model of the Supervision of the OTN -- 3 Proposed Model for the Automatic Provision of the OTN -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References -- Robo-Nurse Healthcare Complete System Using Artificial Intelligence -- 1 Introduction -- 1.1 Related Work -- 2 Research Method -- 2.1 Software Implementation -- 2.2 Hardware Implementation -- 2.3 External Design Implementation -- 3 Results and Discussions -- 4 Conclusion -- References -- Resolving Context Inconsistency Approach Based on Random Forest Tree -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 IoT Data Collection Phase -- 3.2 Context Inconsistency Validator -- 3.3 Best Resolution Selection -- 3.4 Random Forest Tree -- 4 Experimental Results and Evaluations -- 5 Conclusion and Future Directions -- References -- Arduino Line Follower Using Fuzzy Logic Control -- 1 Introduction -- 2 Methodology -- 2.1 Lab Simulation -- 2.2 The ATmega328p Microcontroller -- 2.3 Voltage Regulator -- 2.4 Circuit Diagram Explanation -- 2.5 Microcontroller-Motor Driver IC Interface -- 2.6 Microcontroller-IR Sensor Module Interface -- 2.7 Microcontroller-Variable Resistor Interface -- 2.8 Arduino IDE Interface with Microcontroller -- 3 Summary of Methodology -- 4 Physical Modeling -- 4.1 Block Diagram -- 4.2 Flow Chart -- 4.3 Working Principle -- 5 Result and Analysis -- 6 Conclusion -- References -- Evaluating Adaptive Facade Performance in Early Building Design Stage: An Integrated Daylighting Simulation and Machine Learning. 1 Introduction -- 2 Related Works -- 3 Building as a Machine and Machine Learning in Architecture -- 4 Adaptive Facade -- 5 Methodology -- 5.1 Data Collection: Available Forms of Kinetic Façade Systems -- 5.2 Data Preparation: Applying System Possibility Scores -- 5.3 Data Exploration and Case Study Setup -- 5.4 Prediction Stage: Applying the KNN Algorithm as a Selective Filter -- 6 Systems Modeling and Simulation -- 7 Results and Discussion -- 8 Conclusion -- References -- LTE Downlink Scheduling with Soft Policy Gradient Learning -- 1 Introduction -- 2 Downlink Resource Allocation in LTE -- 3 Related Work -- 4 DSPG Scheduler: The Proposed Scheduling Algorithm -- 4.1 Problem Statement -- 4.2 Model Design -- 5 Simulation Implementation and Results -- 6 Conclusions -- References -- Predicting the Road Accidents Severity Using Artificial Neural Network -- 1 Introduction -- 2 Literature Review -- 3 Dataset -- 4 The Proposed Methodology -- 5 Results and Discussions -- 5.1 Attributes vs Accident Severity -- 5.2 Accident Severity Prediction Results -- 6 Conclusion -- References -- Predicting the Intention to Use Audi and Video Teaching Styles: An Empirical Study with PLS-SEM and Machine Learning Models -- 1 Introduction -- 2 Theoretical Framework -- 2.1 Technology Acceptance Model (TAM) -- 2.2 Flow Theory -- 2.3 Virtual Reality Attributes -- 3 Research Methodology -- 3.1 Data Collection -- 3.2 Personal/Demographic Information -- 3.3 Study Instrument -- 3.4 Survey Structure -- 4 Findings and Discussion -- 4.1 Data Analysis -- 4.2 Convergent Validity -- 4.3 Discriminant Validity -- 4.4 Hypotheses Testing Using PLS-SEM -- 4.5 Hypothesis Testing Using Machine Learning Algorithms -- 5 Discussion of Results -- References -- Intellgenet Systems and Applications. Immunity of Signals Transmission Using Secured Unequal Error Protection Scheme with Various Packet Format. |
| Record Nr. | UNINA-9910561300503321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advanced Analytics in Power BI with R and Python [[electronic resource] ] : Ingesting, Transforming, Visualizing / / by Ryan Wade
| Advanced Analytics in Power BI with R and Python [[electronic resource] ] : Ingesting, Transforming, Visualizing / / by Ryan Wade |
| Autore | Wade Ryan |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Berkeley, CA : , : Apress : , : Imprint : Apress, , 2020 |
| Descrizione fisica | 1 online resource (XLVI, 391 p. 84 illus.) |
| Disciplina | 001.4226028566 |
| Soggetto topico |
Microsoft software
Microsoft .NET Framework Quantitative research Big data Microsoft Data Analysis and Big Data Big Data |
| ISBN | 1-4842-5829-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I. Creating Custom Data Visualizations using R -- 1. The Grammar of Graphics -- 2. Creating R custom visuals in Power BI using ggplot2 -- Part II. Ingesting Data into the Power BI Data Model using R and Python -- 3. Reading CSV Files -- 4. Reading Excel Files -- 5. Reading SQL Server Data -- 6. Reading Data into the Power BI Data Model via an API -- Part III. Transforming Data using R and Python.-7. Advanced String Manipulation and Pattern Matching -- 8. Calculated Columns using R and Python -- Part IV. Machine Learning & AI in Power BI using R and Python -- 9. Applying Machine Learning and AI to your Power BI Data Models -- 10. Productionizing Data Science Models and Data Wrangling Scripts. . |
| Record Nr. | UNINA-9910427050203321 |
Wade Ryan
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| Berkeley, CA : , : Apress : , : Imprint : Apress, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advanced Applications of Blockchain Technology [[electronic resource] /] / edited by Shiho Kim, Ganesh Chandra Deka
| Advanced Applications of Blockchain Technology [[electronic resource] /] / edited by Shiho Kim, Ganesh Chandra Deka |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (X, 278 p. 93 illus., 58 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Studies in Big Data |
| Soggetto topico |
Computational intelligence
Computer security Big data Computational Intelligence Systems and Data Security Big Data Privacy |
| ISBN | 981-13-8775-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction to Blockchain Technology and IoT -- IoT, AI, and Blockchain: Implementation perspectives -- Blockchain Technologies for IoT -- Blockchain Technology Use Cases -- Blockchain meets CyberSecurity: Security, Privacy, Challenges and Opportunity -- On the Role of Blockchain Technology in Internet of Things -- Blockchain of Things (BCoT): The Fusion of Blockchain and IoT Technologies -- Blockchain Architecture -- Authenticating IoT Devices with Blockchain -- Security & Privacy Issues of Block chain Technology -- Supply Chain Management in Agriculture Using Blockchain and IoT -- Blockchain Technologies and Artificial Intelligence -- Blockchain Hands on for Developing Genesis Block. |
| Record Nr. | UNINA-9910484022203321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advanced Computational Methods in Energy, Power, Electric Vehicles, and Their Integration [[electronic resource] ] : International Conference on Life System Modeling and Simulation, LSMS 2017 and International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2017, Nanjing, China, September 22-24, 2017, Proceedings, Part III / / edited by Kang Li, Yusheng Xue, Shumei Cui, Qun Niu, Zhile Yang, Patrick Luk
| Advanced Computational Methods in Energy, Power, Electric Vehicles, and Their Integration [[electronic resource] ] : International Conference on Life System Modeling and Simulation, LSMS 2017 and International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2017, Nanjing, China, September 22-24, 2017, Proceedings, Part III / / edited by Kang Li, Yusheng Xue, Shumei Cui, Qun Niu, Zhile Yang, Patrick Luk |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XX, 815 p. 407 illus.) |
| Disciplina | 006.3 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Computer simulation
Artificial intelligence Special purpose computers Big data Simulation and Modeling Artificial Intelligence Special Purpose and Application-Based Systems Big Data |
| ISBN | 981-10-6364-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Biomedical Signal Processing -- Computational Methods in Organism Modeling -- Medical Apparatus and Clinical Applications -- Bionics Control Methods, Algorithms and Apparatus -- Modeling and Simulation of Life Systems -- Data Driven Analysis -- Image and Video Processing -- Advanced Fuzzy and Neural Network Theory and Algorithms -- Advanced Evolutionary Methods and Applications -- Advanced Machine Learning Methods and Applications -- Intelligent Modeling, Monitoring, and Control of Complex Nonlinear Systems -- Advanced Methods for Networked Systems -- Control and Analysis of Transportation Systems -- Advanced Sliding Mode Control and Applications -- Advanced Analysis of New Materials and Devices -- Computational Intelligence in Utilization of Clean and Renewable Energy Resources -- Intelligent Methods for Energy Saving and Pollution Reduction -- Intelligent Methods in Developing Electric Vehicles, Engines and Equipment -- Intelligent Computing and Control in Power Systems -- Modeling, Simulation and Control in Smart Grid and Microgrid -- Optimization Methods; Computational Methods for Sustainable Environment. |
| Record Nr. | UNINA-9910254837203321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advanced Computing and Systems for Security [[electronic resource] ] : Volume Eleven / / edited by Rituparna Chaki, Agostino Cortesi, Khalid Saeed, Nabendu Chaki
| Advanced Computing and Systems for Security [[electronic resource] ] : Volume Eleven / / edited by Rituparna Chaki, Agostino Cortesi, Khalid Saeed, Nabendu Chaki |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (148 pages) |
| Disciplina | 005.8 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Signal processing Image processing Speech processing systems Computer security Optical data processing Big data Computational Intelligence Signal, Image and Speech Processing Systems and Data Security Computer Imaging, Vision, Pattern Recognition and Graphics Big Data |
| ISBN | 981-15-5747-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A New Graph Polynomial and Generalized Tutte-Grothendieck Invariant From Quantum Circuits -- Dimensionality reduction of hyperspectral images: Cryptanalysis of a Centralized Location-sharing Scheme for Mobile Online Social Networks -- Bounded Version Vectors using MazurkiewiczTraces -- Intents Analysis of Android Apps for Confidentiality Leakage Detection -- Fingerprint and Keystroke dynamics fusion in multimodal biometrics system -- QoS Enhancement in WBAN with Twin Coordinators -- A Distributed Power Control Scheme for Device-to-Device Communication in Cellular Networks -- An Application of Block-Chain in Examination System, a Case Study -- A Study on Energy Efficient Routing Protocols for Wireless Sensor Networks. |
| Record Nr. | UNINA-9910484259603321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advanced Computing and Systems for Security [[electronic resource] ] : Volume Ten / / edited by Rituparna Chaki, Agostino Cortesi, Khalid Saeed, Nabendu Chaki
| Advanced Computing and Systems for Security [[electronic resource] ] : Volume Ten / / edited by Rituparna Chaki, Agostino Cortesi, Khalid Saeed, Nabendu Chaki |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (X, 167 p. 65 illus., 29 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Signal processing Image processing Speech processing systems Computer security Optical data processing Big data Computational Intelligence Signal, Image and Speech Processing Systems and Data Security Computer Imaging, Vision, Pattern Recognition and Graphics Big Data |
| ISBN | 981-13-8969-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part 1: Security Systems -- Chapter 1. A Lightweight Security Protocol for IoT using Merkle Hash Tree and Chaotic Cryptography -- Chapter 2. A Quantitative Methodology for Business Process-based Data Privacy Risk Computation -- Chapter 3. Architectural Design Based Compliance Verification for IoT Enabled Secure Advanced Metering Infrastructure in Smart Grid -- Chapter 4. A Novel Approach to Human Recognition Based on Finger Geometry -- Chapter 5. Biometric Fusion System Using Face and Voice Recognition -- Part 2: Pattern Recognition and Imaging -- Chapter 6. A Multi-Class Image Classifier for Assisting in Tumor Detection of Brain Using Deep Convolution Neural Network -- Chapter 7. Determining Perceptual Similarity Among Readers Based on Eyegaze Dynamics -- Part 3: High Performance Computing -- Chapter 8. 2D Qubit Placement of Quantum Circuits Using LONGPATH -- Chapter 9. Debugging Errors in Microfluidic Executions -- Chapter 10. Effect of Volumetric Split-Errors on Reactant-Concentration During Sample Preparation with Microfluidic Biochips. |
| Record Nr. | UNINA-9910484231703321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advanced Computing and Systems for Security [[electronic resource] ] : Volume Twelve / / edited by Rituparna Chaki, Agostino Cortesi, Khalid Saeed, Nabendu Chaki
| Advanced Computing and Systems for Security [[electronic resource] ] : Volume Twelve / / edited by Rituparna Chaki, Agostino Cortesi, Khalid Saeed, Nabendu Chaki |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (148 pages) |
| Disciplina | 005.8 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Signal processing Image processing Speech processing systems Computer security Optical data processing Big data Computational Intelligence Signal, Image and Speech Processing Systems and Data Security Computer Imaging, Vision, Pattern Recognition and Graphics Big Data |
| ISBN | 981-15-2930-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Automatic caption generation of retinal diseases with self trained RNN merge model -- Dimensionality reduction of hyperspectral images: A data driven approach for band selection -- Comment-Mine -- A Semantic Search Approach to Program Comprehension from Code Comments -- Biomarker Gene Identification using a Quantum Inspired Clustering Approach -- Shot Classification and Replay Detection in Broadcast Soccer Video -- A Novel Automated Blood Cell Counting Method Based on Deconvolution and Convolution and Its Application to Neural Networks -- A citizen centred sentiment analysis towards India's critically endangered Avian and Mammalian species -- Methodology for Generating Synthetic Time-dependant Probabilistic Speed Profiles -- A Multi-scale Patch-based Deep learning system for Polyp Segmentation -- Object detection in rainy condition from video using YOLO based deep learning model -- Visualisation of the evacuation process including people with heart diseases. |
| Record Nr. | UNINA-9910483889903321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advanced Computing and Systems for Security [[electronic resource] ] : Volume Nine / / edited by Rituparna Chaki, Agostino Cortesi, Khalid Saeed, Nabendu Chaki
| Advanced Computing and Systems for Security [[electronic resource] ] : Volume Nine / / edited by Rituparna Chaki, Agostino Cortesi, Khalid Saeed, Nabendu Chaki |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (117 pages) |
| Disciplina | 005.8 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Signal processing Image processing Speech processing systems Computer security Optical data processing Big data Computational Intelligence Signal, Image and Speech Processing Systems and Data Security Computer Imaging, Vision, Pattern Recognition and Graphics Big Data |
| ISBN | 981-13-8962-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part 1: WSN & IoT Applications -- Chapter 1. Fuzzy Logic-based Range-free Localization for Wireless Sensor Network in Agriculture -- Chapter 2. End-User Position Driven Small Base Station Placement for Indoor Communication -- Chapter 3. ZoBe: Zone oriented Bandwidth estimator for Efficient IoT Networks -- Part 2: Software Engineering and Formal Specification for Secured Software Systems -- Chapter 4. Extracting Business Compliant Finite State Models From i* Models -- Chapter 5. Behavioral Analysis of Service Composition Patterns in ECB using Petri Net Based Approach -- Part 3: VLSI and Graph Algorithms -- Chapter 6. Generation of Simple, Connected, Non-Isomorphic Random Graphs -- Chapter 7. Bottleneck Crosstalk Minimization in Three-Layer Channel Routing -- Chapter 8. Arithmetic Circuits using Reversible Logic: A Survey Report. |
| Record Nr. | UNINA-9910484235903321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Soggetto topico
-
Big Data
(417)
- Big data (411)
- Computational Intelligence (130)
- Artificial Intelligence (122)
- Artificial intelligence (122)