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Augmented Reality, Virtual Reality & Semantic 3D Reconstruction
| Augmented Reality, Virtual Reality & Semantic 3D Reconstruction |
| Autore | Lv Zhihan |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (304 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology |
| Soggetto non controllato |
feature tracking
superpixel structure from motion three-dimensional reconstruction local feature multi-view stereo construction hazard safety education photoreality virtual reality anatomization audio classification olfactory display deep learning transfer learning inception model augmented reality higher education scientific production web of science bibliometric analysis scientific mapping applications in subject areas interactive learning environments 3P model primary education educational technology mobile lip reading system lightweight neural network face correction virtual reality (VR) computer vision projection mapping 3D face model super-resolution radial curve Dynamic Time Warping semantic 3D reconstruction eye-in-hand vision system robotic manipulator probabilistic fusion graph-based refinement 3D modelling 3D representation game engine laser scanning panoramic photography super-resolution reconstruction generative adversarial networks dense convolutional networks texture loss WGAN-GP orientation positioning viewpoint image matching algorithm transformation ADHD EDAH assessment continuous performance test Photometric Stereo (PS) 3D reconstruction fully convolutional network (FCN) semi-immersive virtual reality children cooperative games empowerment perception motor planning problem-solving area of interest wayfinding spatial information one-shot learning gesture recognition GREN skeleton-based 3D composition pre-visualization stereo vision 360° video |
| ISBN | 3-0365-6062-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910639985103321 |
Lv Zhihan
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Electrochemical Exfoliation of Graphene and Its Derivatives : Commercial Applications / / edited by Raju Khan, Neeraj Kumar, Mohd. Abubakar Sadique, Arpana Parihar
| Electrochemical Exfoliation of Graphene and Its Derivatives : Commercial Applications / / edited by Raju Khan, Neeraj Kumar, Mohd. Abubakar Sadique, Arpana Parihar |
| Autore | Khan Raju |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (350 pages) |
| Disciplina |
530.41
620.19 |
| Altri autori (Persone) |
KumarNeeraj
SadiqueMohd. Abubakar PariharArpana |
| Collana | Engineering Materials |
| Soggetto topico |
Condensed matter
Biophysics Materials Chemistry Materials - Analysis Carbon Two-dimensional Materials Bioanalysis and Bioimaging Materials Chemistry Materials Characterization Technique Carbon Materials |
| ISBN |
9789819721283
9819721288 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Overview of electrochemical exfoliation approaches -- 2. Advantages of electrochemical exfoliation method over conventional methods -- 3. Graphene and its derivatives: various routes of synthesis -- 4. Structure and electrochemical properties of graphene, derivatives and its nanocomposites -- 5. Electrochemical exfoliation a green approach: Waste to wealth -- 6. Mechanism of synthesis for graphene and its derivatives by electrochemical exfoliation -- 7. Unique characteristics of electrochemically exfoliated multi-dimensional graphene and its derivatives -- 8. Electrochemistry and energy storage applications of graphene and its derivatives -- 9. Applications of electrochemically exfoliated graphene and its derivatives in the field of Biosensing and Bioimaging -- 10. Electrochemical exfoliation of graphene and its derivatives and its extended applications in therapeutics -- 11. Methodology advancements for bulk production and commercialization of graphene and its derivatives -- 12. Challenges and future opportunities in the field of electrochemical exfoliation techniques. |
| Record Nr. | UNINA-9910861090303321 |
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Khan Raju
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Intelligent data analysis for COVID-19 pandemic / / M. Niranjanamurthy, Siddhartha Bhattacharyya, Neeraj Kumar, editors
| Intelligent data analysis for COVID-19 pandemic / / M. Niranjanamurthy, Siddhartha Bhattacharyya, Neeraj Kumar, editors |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (377 pages) |
| Disciplina | 362.1962414 |
| Collana | Algorithms for Intelligent Systems |
| Soggetto topico |
COVID-19 (Disease) - Economic aspects
COVID-19 (Disease) - Health aspects |
| ISBN | 981-16-1574-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- Machine Learning-Based Ensemble Approach for Predicting the Mortality Risk of COVID-19 Patients: A Case Study -- 1 Introduction -- 2 Literature Review -- 3 Dataset and Methodology Used -- 3.1 Dataset Description and Preparation -- 3.2 Data Preprocessing -- 3.3 Classification and Ensembling Approaches -- 4 Ensembling Approaches -- 4.1 Boosting -- 4.2 Bagging -- 5 Experiments and Results -- 5.1 Feature Selection of Patient Attributes -- 5.2 Performance of Individual Classifiers -- 6 Conclusion -- References -- Role of Internet of Health Things (IoHTs) and Innovative Internet of 5G Medical Robotic Things (IIo-5GMRTs) in COVID-19 Global Health Risk Management and Logistics Planning -- 1 Introduction -- 1.1 Background of the Study -- 1.2 Aims and Objective of the Study -- 2 Literature Review -- 3 Research Design and Implementation -- 3.1 Research Analysis -- 3.2 Research Discussion -- 4 Future Research Focus -- 5 Recommendation -- 6 Conclusion -- References -- Battling COVID-19 with Process Model of Integrated Digital Technology: An Analysis of Qualitative Data -- 1 Introduction -- 2 Research Design and Structure -- 3 Digital Technology to Combat COVID-19 -- 3.1 Mobile Applications and COVID-19 -- 3.2 Artificial Intelligence, Internet of Things (IoT), Big Data Analytics, and COVID 19 -- 3.3 Social Media and COVID -- 4 Summarization of Digital Technology Applications and COVID-19 -- 5 Process Model of Integrated Digital Technology -- 6 Conclusion -- References -- High-Fidelity Intelligence Ventilator to Help Infect with COVID-19 Based on Artificial Intelligence -- 1 Introduction -- 2 Operating and Revision Modes -- 3 Design and Condition of the Instrument -- 4 Materials and Technology -- 4.1 Typical Parts Needed -- 4.2 Arduino Nano Compatible V3.0 ATmega328.
4.3 Electronic Motor Speed Controller -- 4.4 Wi-Fi Module -- 5 Results and Discussion -- 6 Conclusion -- References -- Boon of Artificial Intelligence in Diagnosis of COVID-19 -- 1 Introduction -- 2 Novel Coronavirus (SARS-CoV-2) -- 3 Evolution of Artificial Intelligence -- 3.1 Strong AI -- 3.2 Weak AI -- 4 Applications of Computational Techniques -- 4.1 Speed Up Diagnosis -- 4.2 Computerized Tracking -- 4.3 Tracking of Infected Individual -- 4.4 Prediction of Incidence Rate and Mortality Rate -- 4.5 Designing and Development of New Drugs and Vaccines -- 4.6 Lowering the Work Load -- 4.7 Prevention of Infectious Disease -- 5 Traditional Diagnostic Methodology -- 5.1 Lateral Flow Immunoassay (LFIA) -- 5.2 Chemiluminescent Immunoassay (CLIA) -- 5.3 Neutralization Assay -- 6 Machine Learning -- 6.1 Algorithms -- 6.2 Random Forest -- 7 Contact Tracing -- 8 Detection Through Smell -- 9 Conclusion -- References -- Artificial Intelligence and Big Data Solutions for COVID-19 -- 1 Introduction -- 2 The COVID-19 Pandemic -- 3 AI and Big Data Techniques for COVID-19 -- 4 AI and Big Data Applications for COVID-19 -- 4.1 Early Detecting and Finding COVID-19 Cases -- 4.2 Early Detecting and Finding COVID-19 Cases -- 4.3 Following Up Contacts -- 4.4 Projection of Cases and Moralities -- 4.5 Reducing the Workload on Healthcare Workers -- 4.6 Prevention of the Infections -- 5 A Proposed Model of AI and Big Data for COVID-19: Smartphone for Surveillance -- 6 Discussions -- 7 Future Insights -- 8 Conclusions -- References -- Emerging Trends in Higher Education During Pandemic Covid-19: An Impact Study from West Bengal -- 1 Introduction -- 2 Research Background Literature -- 3 Methodology -- 3.1 Research Gaps -- 3.2 Research Objectives -- 3.3 Sample Design -- 3.4 Research Approach -- 3.5 Research Tools Usage in Current Research -- 3.6 SXUK Case Study Process. 4 Research Findings and Discussion -- 4.1 Teaching-Learning Context During Covid-19 -- 4.2 Content Development Orientation -- 4.3 ICT Technology Strategies in HEIs -- 4.4 "Big Five" Strategies -- 4.5 Technology-CI Adapted Teaching-Learning Strategies -- 4.6 Higher Educational Institutes Wise -- 4.7 CI Awareness and Application in HEIs -- 4.8 Computational Intelligence-ICT Factors Confluence -- 4.9 CI-Based HEIs Cluster Membership -- 5 Case Organization: SXUK -- 5.1 Introduction -- 5.2 Historical Millstones of SXUK -- 5.3 SXUK Organogram -- 5.4 AI-CI Interface Strategies for SXUK -- 6 Conclusion -- References -- COVID-19: Virology, Epidemiology, Diagnostics and Predictive Modeling -- 1 Introduction -- 2 Virology of SARS-CoV-2 -- 3 Diagnostics and Current Line of Treatment of Coronavirus Disease-2019 (COVID-19) -- 4 Comparison of Population Distribution of India, USA and Spain -- 5 Mathematical Modeling -- 6 Concluding Remarks -- References -- Improved Estimation in Logistic Regression Through Quadratic Bootstrap Approach: An Application in Indian Agricultural E-learning System During COVID-19 Pandemic -- 1 Introduction -- 2 Logistic Regression Model -- 2.1 Preliminaries -- 2.2 Identification of the Most Influential Variable -- 2.3 Estimation in Logistic Regression Model -- 2.4 Goodness of Fit -- 2.5 Predictive Ability -- 2.6 Comparison Measures -- 3 Empirical Results -- 3.1 Data and Implementation -- 3.2 Comparative Assessment Between MLE and Quadratic Bootstrap Estimation -- 3.3 Outcomes of the Simulation Study -- 4 Conclusion -- References -- COVID-19 and Stock Markets: Deaths and Strict Policies -- 1 Introduction -- 2 COVID-19 and Its Macroeconomic Effects -- 3 COVID-19 and Stock Markets -- 4 Data and Econometric Model -- 4.1 Diagnostic Statistics and Correlation Analysis -- 4.2 Analysis Results -- 5 Conclusion -- References. Artificial Intelligence Techniques in Medical Imaging for Detection of Coronavirus (COVID-19/SARS-COV-2): A Brief Survey -- 1 Introduction -- 2 Literature Survey -- 3 Artificial Intelligence -- 4 Machine Learning -- 5 Neural Networks -- 5.1 Deep Learning -- 5.2 Transfer Learning -- 5.3 Convolutional Neural Networks -- 6 CNN Algorithms and Methods Used in the Survey -- 6.1 Inception V3 -- 6.2 ResNet-50 -- 6.3 Inception-ResNet-v2 -- 6.4 VGG-19 -- 6.5 MobileNet -- 7 Materials and Methods -- 7.1 Dataset -- 7.2 Performance Analysis Parameters -- 8 Results and Discussions -- 9 Conclusion and Future Challenges -- References -- A Travelling Disinfection-Man Problem (TDP) for COVID-19: A Nonlinear Binary Constrained Gaining-Sharing Knowledge-Based Optimization Algorithm -- 1 Coronavirus (COVID-19): An Overview -- 2 Coronavirus Decontamination Planning Process -- 3 Coronavirus Travelling Disinfection-Man Problem (TDP) -- 4 The Travelling Salesman Problem (TSP) and Its Variations -- 5 Mathematical Model Formulation for the Travelling Disinfection-Man Problem -- 6 Real Application Case Study Application: Ain Shams University, Cairo -- 7 Artificial Intelligence Techniques in Optimization -- 8 Proposed Methodology -- 8.1 Overview of Gaining-Sharing Knowledge-Based Optimization Algorithm (GSK) -- 8.2 Discrete Binary Gaining-Sharing Knowledge-Based Optimization Algorithm (DBGSK) -- 9 Experimental Results -- 10 Conclusions -- 11 Points for Future Researches -- References -- COVID-19 Lock Down Impact on Mental Health: A Cross-Sectional Online Survey from Kerala, India -- 1 Introduction -- 1.1 Motivation for Doing the Research -- 2 Review of Literature -- 3 Methods -- 4 Results and Discussions -- 4.1 Types of Activities -- 4.2 Mental Health Issues and Eating Behaviour -- 4.3 Awareness Among People -- 5 Conclusion -- References. Analysis, Modelling and Prediction of COVID-19 Outbreaks Using Machine Learning Algorithms -- 1 Introduction -- 2 COVID-19 Around the Global -- 3 Machine Learning and Its Types -- 3.1 Supervised Learning -- 4 Implementation -- 4.1 Evaluation Metrics -- 5 Time Series Data set -- 5.1 Analysis, Modelling and Prediction of COVID-19 -- 5.2 Confirmed Cases and Death Cases as on 20 July 2020-World -- 5.3 Confirmed Cases and Death Cases as on 20th July 2020-India -- 5.4 Model of Machine Learning Algorithm -- 5.5 Predicting the Outgrowth in the Next 3 Months-India -- 6 Conclusion -- References -- Tracking and Analysis of Corona Disease Using Intelligent Data Analysis -- 1 Introduction -- 2 AI Versus COVID-19 -- 2.1 Prediction and Data Sharing -- 2.2 R& -- D Sector -- 2.3 Deception -- 2.4 Monitoring -- 2.5 Data Overload -- 2.6 Arrangement of Automated Vehicles -- 2.7 Variances Between the AI Techniques [1] -- 3 Using AI to Detect, Respond, and Recover from COVID-19 -- 3.1 Computer-Based Intelligence for COVID-19 Medical Response -- 4 AI for COVID-19 Social Control -- 4.1 Man-Made Reasoning in the Battle Against COVID-19 -- 4.2 Information Access -- 4.3 Security Ensuring Applications -- 5 How Artificial Intelligence Applications can Contain Coronavirus COVID-19 -- 5.1 Man-Made Reasoning in the Battle Against COVID-19 -- 5.2 Information Access -- 5.3 Security Ensuring Applications -- 6 Conclusion -- References -- Index. |
| Record Nr. | UNINA-9910488705703321 |
| Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Multimedia Big Data Computing for IoT Applications : Concepts, Paradigms and Solutions / / edited by Sudeep Tanwar, Sudhanshu Tyagi, Neeraj Kumar
| Multimedia Big Data Computing for IoT Applications : Concepts, Paradigms and Solutions / / edited by Sudeep Tanwar, Sudhanshu Tyagi, Neeraj Kumar |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (xiv, 477 pages) |
| Disciplina | 005.7 |
| Collana | Intelligent Systems Reference Library |
| Soggetto topico |
Computational intelligence
Computer security Big data Multimedia systems Application software Computational Intelligence Systems and Data Security Big Data Multimedia Information Systems Information Systems Applications (incl. Internet) |
| ISBN | 981-13-8759-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Multimedia Big data computing for IoT -- Energy Conservation in MMBD Computing and IoT – A Challenge -- An Architecture for the Real-Time Data Stream Monitoring in IoT -- Deep learning for Multimedia data in IoT -- Random Forest based Sarcastic Tweet Classification using multiple feature Collection -- Peak Average Power Ratio reduction in FBMC using SLM & PTS techniques -- Intelligent Personality Analysis on Indicators in IoT-MMBD Enabled Environment -- Data Reduction in MMBD Computing -- Large Scale MMBD Management and Retrieval -- Data Reduction Technique for Capsule Endoscopy -- Multimedia Social Big Data: Mining -- Advertisement prediction in social media environment using big data framework. |
| Record Nr. | UNINA-9910484861903321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Next Generation Computing Technologies on Computational Intelligence : 4th International Conference, NGCT 2018, Dehradun, India, November 21–22, 2018, Revised Selected Papers / / edited by Manish Prateek, Durgansh Sharma, Rajeev Tiwari, Rashmi Sharma, Kamal Kumar, Neeraj Kumar
| Next Generation Computing Technologies on Computational Intelligence : 4th International Conference, NGCT 2018, Dehradun, India, November 21–22, 2018, Revised Selected Papers / / edited by Manish Prateek, Durgansh Sharma, Rajeev Tiwari, Rashmi Sharma, Kamal Kumar, Neeraj Kumar |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (xix, 375 pages) : illustrations |
| Disciplina | 004.3 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Computer science
Application software Artificial intelligence Computer Science, general Information Systems Applications (incl. Internet) Artificial Intelligence |
| ISBN | 981-15-1718-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Image Processing, Pattern Analysis and Machine Vision -- Information and Data Convergence -- Disruptive Technologies for Future -- E-Governance and Smart World. |
| Record Nr. | UNINA-9910357842903321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of First International Conference on Computing, Communications, and Cyber-Security (IC4S 2019) / / edited by Pradeep Kumar Singh, Wiesław Pawłowski, Sudeep Tanwar, Neeraj Kumar, Joel J. P. C. Rodrigues, Mohammad Salameh Obaidat
| Proceedings of First International Conference on Computing, Communications, and Cyber-Security (IC4S 2019) / / edited by Pradeep Kumar Singh, Wiesław Pawłowski, Sudeep Tanwar, Neeraj Kumar, Joel J. P. C. Rodrigues, Mohammad Salameh Obaidat |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (886 pages) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Computational intelligence
Machine learning Electrical engineering Data protection Computational Intelligence Machine Learning Communications Engineering, Networks Security |
| ISBN | 981-15-3369-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part 1: Communication & Network Technologies -- Chapter 1. State Of The Art: A Review on Vehicular Communications, Impact of 5g, Fractal Antennas for Future Communication -- Chapter 2. Energy Enhancement of TORA and DYMO by Optimization of Hello Messaging using BFO for MANET's -- Chapter 3. Horseshoe Shaped Multiband Antenna for Wireless Application -- Chapter 4. A Review Paper on Performance Analysis of IEEE 802.11e -- Chapter 5. Voice Control IOT Devices Framework for Smart Home -- Chapter 6. Comprehensive Analysis of Social based Opportunistic Routing Protocol: A Study -- Chapter 7. An Efficient Delay based Load Balancing using AOMDV in MANET -- Chapter 8. Metaheuristic-based Intelligent Solutions Searching Algorithms of Ant Colony Optimization and Backpropagation in Neural Networks -- Chapter 9. Evaluating Cohesion Score with Email Clustering.-Chapter 10. Congestion Control for Named Data Networking Based Wireless Ad-hoc Network.-Chapter 11. A Comparative review of various techniques for Image Splicing Detection and Localization..-Chapter 12. Analysis and Synthesis of Performance Parameter of Rectangular Patch Antenna -- Part 2: Advanced Computing Technologies & Latest Electrical & Electronics Trends -- Chapter 13. Fog Computing Research Opportunities & Challenges: A Comprehensive Survey -- Chapter 14. IIGPTS: IoT-based framework for Intelligent Green Public Transportation System -- Chapter 15. Integrating the AAL CasAware platform within an IoT ecosystem, leveraging the INTER-IoT approach. . |
| Record Nr. | UNINA-9910482986403321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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