Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
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] 68T45 - Machine vision and scene understanding [MSC 2020] 68T07 - Artificial neural networks and deep learning [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 | ||
| ||
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 | ||
| ||
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. | UNINA-9910743294803321 |
| Bielefeld : , : transcript Verlag, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
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
|
||
| Cham, : Birkhäuser, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Bioimage Data Analysis Workflows ‒ Advanced Components and Methods [[electronic resource] /] / edited by Kota Miura, Nataša Sladoje
| Bioimage Data Analysis Workflows ‒ Advanced Components and Methods [[electronic resource] /] / 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 |
|
Miura Kota
|
||
| Cham, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
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 | ||
| ||
Compressed sensing and its applications : Third International MATHEON Conference 2017 / Holger Boche ... [et al.] editors
| Compressed sensing and its applications : Third International MATHEON Conference 2017 / Holger Boche ... [et al.] editors |
| Pubbl/distr/stampa | Cham, : Birkhäuser, 2019 |
| Descrizione fisica | xvii, 295 p. : ill. ; 24 cm |
| Soggetto topico |
90C90 - Applications of mathematical programming [MSC 2020]
68P30 - Coding and information theory (compaction, compression, models of communication, encoding schemes, etc.) [MSC 2020] 94Axx - Communication, information [MSC 2020] |
| Soggetto non controllato |
Compressed Sensing
Compressed sensing 2019 Compressed sensing theory and applications Deep Learning Deep learning compressed sensing Generalization error machine learning Information and communication, circuits MATHEON conference Machine learning Quantized compressed sensing Signal sensing book |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0126787 |
| Cham, : Birkhäuser, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Cybersecurity in Digital Transformation : Scope and Applications / Dietmar P.F. Möller
| Cybersecurity in Digital Transformation : Scope and Applications / Dietmar P.F. Möller |
| Autore | Möller, Dietmar P. F. |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | xix, 114 p. : ill. ; 24 cm |
| Soggetto topico |
68-XX - Computer science [MSC 2020]
94-XX - Information and communication theory, circuits [MSC 2020] |
| Soggetto non controllato |
Anomaly Detection
Attach Models and Scenarios Cyber Threat Intelligence Cybersecurity Cybersecurity Leadership Cybersecurity Ontology Deep Learning Digital Transformation Intrusion Detection and Intrusion Prevention Machine learning |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0248955 |
|
Möller, Dietmar P. F.
|
||
| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Deep Learning Architectures : A Mathematical Approach / Ovidiu Calin
| Deep Learning Architectures : A Mathematical Approach / Ovidiu Calin |
| Autore | Calin, Ovidiu |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | xxx, 760 p. : ill. ; 24 cm |
| Soggetto topico |
68-XX - Computer science [MSC 2020]
92B20 - Neural networks for/in biological studies, artificial life and related topics [MSC 2020] 68T07 - Artificial neural networks and deep learning [MSC 2020] |
| Soggetto non controllato |
Boltzmann machine
Deep Learning Entropy Fisher Information Metric Kullback-Leibler Divergence Machine learning Neural networks |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0248977 |
|
Calin, Ovidiu
|
||
| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Deep Learning based Vehicle Detection in Aerial Imagery
| Deep Learning based Vehicle Detection in Aerial Imagery |
| Autore | Wilko Sommer Lars |
| Pubbl/distr/stampa | Karlsruhe, : KIT Scientific Publishing, 2022 |
| Descrizione fisica | 1 electronic resource (276 p.) |
| Collana | Karlsruher Schriften zur Anthropomatik |
| Soggetto topico | Maths for computer scientists |
| Soggetto non controllato |
Objektdetektion
Neuronale Netze Luftbilddaten Object Detection Deep Learning Aerial Imagery |
| ISBN | 1000135415 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910548274803321 |
|
Wilko Sommer Lars
|
||
| Karlsruhe, : KIT Scientific Publishing, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
