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3D Point Cloud Analysis : Traditional, Deep Learning, and Explainable Machine Learning Methods / Shan Liu ... [et al.]
| 3D Point Cloud Analysis : Traditional, Deep Learning, and Explainable Machine Learning Methods / Shan Liu ... [et al.] |
| Pubbl/distr/stampa | Cham, : Springer, 2021 |
| Descrizione fisica | xiv, 146 p. : ill. ; 24 cm |
| Soggetto topico |
68-XX - Computer science [MSC 2020]
68T05 - Learning and adaptive systems in artificial intelligence [MSC 2020] 68T07 - Artificial neural networks and deep learning [MSC 2020] 68T45 - Machine vision and scene understanding [MSC 2020] |
| Soggetto non controllato |
3D computer vision
3D object detection 3D object recognition Deep Learning Explainable machine learning Machine learning ModelNet40 Point cloud analysis Point cloud classification Point cloud part segmentation Point cloud registration PointHop R-PointHop Saab transform ShapeNet Successive subspace learning Unsupervised learning |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0274505 |
| Cham, : Springer, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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3D Point Cloud Analysis : Traditional, Deep Learning, and Explainable Machine Learning Methods / Shan Liu ... [et al.]
| 3D Point Cloud Analysis : Traditional, Deep Learning, and Explainable Machine Learning Methods / Shan Liu ... [et al.] |
| Pubbl/distr/stampa | Cham, : Springer, 2021 |
| Descrizione fisica | xiv, 146 p. : ill. ; 24 cm |
| Soggetto topico |
68-XX - Computer science [MSC 2020]
68T05 - Learning and adaptive systems in artificial intelligence [MSC 2020] 68T07 - Artificial neural networks and deep learning [MSC 2020] 68T45 - Machine vision and scene understanding [MSC 2020] |
| Soggetto non controllato |
3D computer vision
3D object detection 3D object recognition Deep Learning Explainable machine learning Machine learning ModelNet40 Point cloud analysis Point cloud classification Point cloud part segmentation Point cloud registration PointHop R-PointHop Saab transform ShapeNet Successive subspace learning Unsupervised learning |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00274505 |
| Cham, : Springer, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
AI - Limits and Prospects of Artificial Intelligence / / ed. by Peter Klimczak, Christer Petersen
| AI - Limits and Prospects of Artificial Intelligence / / ed. by Peter Klimczak, Christer Petersen |
| Pubbl/distr/stampa | Bielefeld : , : transcript Verlag, , [2023] |
| Descrizione fisica | 1 online resource (290 p.) |
| Collana | KI-Kritik |
| Soggetto topico | SOCIAL SCIENCE / Media Studies |
| Soggetto non controllato |
Algorithms
Big Data Computer Sciences Deep Learning Digital Media Ethics Internet Machine Learning Media Philosophy Media Studies Sociology of Media Technology |
| ISBN | 3-8394-5732-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Editorial -- Contents -- Preface -- Learning Algorithms -- Transgressing the Boundaries -- Limits and Prospects of Ethics in the Context of Law and Society by the Example of Accident Algorithms of Autonomous Driving -- Limits and Prospects of Big Data and Small Data Approaches in AI Applications -- Artificial Intelligence and/as Risk -- When You Can’t Have What You Want -- Man-Machines -- Trends in Explainable Artificial Intelligence for Non-Experts -- Machine Dreaming -- Let’s Fool That Stupid AI -- Authors |
| Record Nr. | UNISA-996545359503316 |
| Bielefeld : , : transcript Verlag, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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AI - Limits and Prospects of Artificial Intelligence / / ed. by Peter Klimczak, Christer Petersen
| AI - Limits and Prospects of Artificial Intelligence / / ed. by Peter Klimczak, Christer Petersen |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Bielefeld : , : transcript Verlag, , [2023] |
| Descrizione fisica | 1 online resource (290 p.) |
| Collana | KI-Kritik |
| Soggetto topico | SOCIAL SCIENCE / Media Studies |
| Soggetto non controllato |
Algorithms
Big Data Computer Sciences Deep Learning Digital Media Ethics Internet Machine Learning Media Philosophy Media Studies Sociology of Media Technology |
| ISBN | 3-8394-5732-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Editorial -- Contents -- Preface -- Learning Algorithms -- Transgressing the Boundaries -- Limits and Prospects of Ethics in the Context of Law and Society by the Example of Accident Algorithms of Autonomous Driving -- Limits and Prospects of Big Data and Small Data Approaches in AI Applications -- Artificial Intelligence and/as Risk -- When You Can’t Have What You Want -- Man-Machines -- Trends in Explainable Artificial Intelligence for Non-Experts -- Machine Dreaming -- Let’s Fool That Stupid AI -- Authors |
| Record Nr. | UNINA-9910743294803321 |
| Bielefeld : , : transcript Verlag, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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An Introduction to Artificial Intelligence Based on Reproducing Kernel Hilbert Spaces / Sergei Pereverzyev
| An Introduction to Artificial Intelligence Based on Reproducing Kernel Hilbert Spaces / Sergei Pereverzyev |
| Autore | Pereverzyev, Sergei |
| Pubbl/distr/stampa | Cham, : Birkhäuser, : Springer, 2022 |
| Descrizione fisica | xiv, 152 p. : ill. ; 24 cm |
| Soggetto non controllato |
Artificial Intelligence
Deep Learning Examples Integral operators Learning theory Linear regularization Tikhonov RKHS deep neural networks Ranking learning Regression learning Regularization theory Reinforcement Learning Reproducing Kernel Hilbert spaces Statistical learning Unsupervised Domain Adaptation |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0276167 |
Pereverzyev, Sergei
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| Cham, : Birkhäuser, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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An Introduction to Artificial Intelligence Based on Reproducing Kernel Hilbert Spaces / Sergei Pereverzyev
| An Introduction to Artificial Intelligence Based on Reproducing Kernel Hilbert Spaces / Sergei Pereverzyev |
| Autore | Pereverzyev, Sergei |
| Pubbl/distr/stampa | Cham, : Birkhäuser, : Springer, 2022 |
| Descrizione fisica | xiv, 152 p. : ill. ; 24 cm |
| Soggetto topico |
62G05 - Nonparametric estimation [MSC 2020]
65C20 - Probabilistic models, generic numerical methods in probability and statistics [MSC 2020] 65J20 - Numerical solutions of ill-posed problems in abstract spaces; regularization [MSC 2020] 68Q32 - Computational learning theory [MSC 2020] 68T05 - Learning and adaptive systems in artificial intelligence [MSC 2020] |
| Soggetto non controllato |
Artificial Intelligence
Deep Learning Examples Integral operators Learning theory Linear regularization Tikhonov RKHS deep neural networks Ranking learning Regression learning Regularization theory Reinforcement Learning Reproducing Kernel Hilbert spaces Statistical learning Unsupervised Domain Adaptation |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00276167 |
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Pereverzyev, Sergei
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| Cham, : Birkhäuser, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Beam Test Calorimeter Prototypes for the CMS Calorimeter Endcap Upgrade : Qualification, Performance Validation and Fast Generative Modelling : Doctoral Thesis accepted by the Rheinisch Westfälische Technische Hochschule, Aachen, Germany / Thorben Quast
| Beam Test Calorimeter Prototypes for the CMS Calorimeter Endcap Upgrade : Qualification, Performance Validation and Fast Generative Modelling : Doctoral Thesis accepted by the Rheinisch Westfälische Technische Hochschule, Aachen, Germany / Thorben Quast |
| Autore | Quast, Thorben |
| Pubbl/distr/stampa | Cham, : Springer, 2021 |
| Descrizione fisica | xxii, 277 p. : ill. ; 24 cm |
| Soggetto non controllato |
Calorimeter
Compact muon solenoid Deep Learning Generative Modelling Large Hadron Collider Particle physics Silicon |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00282286 |
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Quast, Thorben
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| Cham, : Springer, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Big Data Privacy and Security in Smart Cities / Richard Jiang ... [et al.] editors
| Big Data Privacy and Security in Smart Cities / Richard Jiang ... [et al.] editors |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | vi, 248 p. : ill. ; 24 cm |
| Soggetto non controllato |
Cloud Security
Data encryption Deep Learning Forensics and Legislation Machine learning Medical Data Privacy and Security Issues Social media e-Commercial e-Governance |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00283381 |
| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Bioimage Data Analysis Workflows ‒ Advanced Components and Methods / / edited by Kota Miura, Nataša Sladoje
| Bioimage Data Analysis Workflows ‒ Advanced Components and Methods / / edited by Kota Miura, Nataša Sladoje |
| Autore | Miura Kota |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2022 |
| Descrizione fisica | 1 online resource (X, 212 p. 265 illus. in color.) |
| Disciplina | 571.6 |
| Collana | Learning Materials in Biosciences |
| Soggetto topico |
Cytology
Bioinformatics Imaging systems in biology Cell Biology Computational and Systems Biology Biological Imaging Microscòpia electrònica |
| Soggetto genere / forma | Llibres electrònics |
| Soggetto non controllato |
Analyzing Image Data in Biology
Building a Bioimage Analysis Workflow Computational Analysis Chosing the Correct Components for Given Biological Questions Data Handling and Plotting Deep Learning Fast Computation GPU-Acceleration Handling Biological data Machine Learning Phyton Processing Language Understanding Bioimage Analysis Software |
| ISBN | 3-030-76394-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Batch Processing Methods in ImageJ -- Python: Data Handling, Analysis and Plotting -- Building a Bioimage Analysis Workflow Using Deep Learning -- GPU-Accelerating ImageJ Macro Image Processing Workflows Using CLIJ -- How to Do the Deconstruction of Bioimage Analysis Workflows: A Case Study with SurfCut -- i.2.i. with the (Fruit) Fly: Quantifying Position Effect Variegation in Drosophila Melanogaster -- A MATLAB Pipeline for Spatiotemporal Quantification of Monolayer Cell Migration. |
| Record Nr. | UNINA-9910597155503321 |
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Miura Kota
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| Cham, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Black Box Optimization, Machine Learning, and No-Free Lunch Theorems / Panos M. Pardalos, Varvara Rasskazova, Michael N. Vrahatis editors
| Black Box Optimization, Machine Learning, and No-Free Lunch Theorems / Panos M. Pardalos, Varvara Rasskazova, Michael N. Vrahatis editors |
| Pubbl/distr/stampa | Cham, : Springer, 2021 |
| Descrizione fisica | x, 388 p. : ill. ; 24 cm |
| Soggetto topico |
68-XX - Computer science [MSC 2020]
68T05 - Learning and adaptive systems in artificial intelligence [MSC 2020] 00B15 - Collections of articles of miscellaneous specific interest [MSC 2020] 90-XX - Operations research, mathematical programming [MSC 2020] 90C59 - Approximation methods and heuristics in mathematical programming [MSC 2020] |
| Soggetto non controllato |
Black box optimization
Data driven computation Data sciences problems Deep Learning Fuzzy Optimization Machine learning No-free lunch theorems Non-free theorems in machine learning Non-free theorems in optimization Stochastic Optimization Tuning algorithms |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0274601 |
| Cham, : Springer, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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