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] 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 | ||
| ||
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 | ||
| ||
An introduction to statistical learning : with applications in R / Gareth James ... [et al.]
| An introduction to statistical learning : with applications in R / Gareth James ... [et al.] |
| Edizione | [2. ed] |
| Pubbl/distr/stampa | New York, : Springer, 2021 |
| Descrizione fisica | xv, 607 p. : ill. ; 25 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
68T05 - Learning and adaptive systems in artificial intelligence [MSC 2020] 62Cxx - Statistical decision theory [MSC 2020] |
| Soggetto non controllato |
Data Mining
Inference R software Statistical learning Supervised learning Unsupervised learning |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0275551 |
| New York, : Springer, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
An introduction to statistical learning : with applications in R / Gareth James ... [et al.]
| An introduction to statistical learning : with applications in R / Gareth James ... [et al.] |
| Edizione | [2. ed] |
| Pubbl/distr/stampa | New York, : Springer, 2021 |
| Descrizione fisica | xv, 607 p. : ill. ; 25 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62Cxx - Statistical decision theory [MSC 2020] 68T05 - Learning and adaptive systems in artificial intelligence [MSC 2020] |
| Soggetto non controllato |
Data Mining
Inference R software Statistical learning Supervised learning Unsupervised learning |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00275551 |
| New York, : Springer, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Marginal and Functional Quantization of Stochastic Processes / Harald Luschgy, Gilles Pagès
| Marginal and Functional Quantization of Stochastic Processes / Harald Luschgy, Gilles Pagès |
| Autore | Luschgy, Harald |
| Pubbl/distr/stampa | Cham, : Springer, 2023 |
| Descrizione fisica | xviii, 912 p. : ill. ; 24 cm |
| Altri autori (Persone) | Pagès, Gilles |
| Soggetto non controllato |
Cluster algorithms
Continuous-time stochastic processes Discretization Methods Luschgy Graf Numerical Probability Numerical methods in probability Pages Numerical Probability Random vectors Signal processing Signal transmission Space discretizations Unsupervised learning Vector Quantization |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0279517 |
Luschgy, Harald
|
||
| Cham, : Springer, 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Marginal and Functional Quantization of Stochastic Processes / Harald Luschgy, Gilles Pagès
| Marginal and Functional Quantization of Stochastic Processes / Harald Luschgy, Gilles Pagès |
| Autore | Luschgy, Harald |
| Pubbl/distr/stampa | Cham, : Springer, 2023 |
| Descrizione fisica | xviii, 912 p. : ill. ; 24 cm |
| Altri autori (Persone) | Pagès, Gilles |
| Soggetto topico |
46N30 - Applications of functional analysis in probability theory and statistics [MSC 2020]
60-XX - Probability theory and stochastic processes [MSC 2020] 60B11 - Probability theory on linear topological spaces [MSC 2020] 60G15 - Gaussian processes [MSC 2020] 65C30 - Numerical solutions to stochastic differential and integral equations [MSC 2020] |
| Soggetto non controllato |
Cluster algorithms
Continuous-time stochastic processes Discretization Methods Luschgy Graf Numerical Probability Numerical methods in probability Pages Numerical Probability Random vectors Signal processing Signal transmission Space discretizations Unsupervised learning Vector Quantization |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00279517 |
|
Luschgy, Harald
|
||
| Cham, : Springer, 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Neural Networks and Deep Learning : A Textbook / Charu C. Aggarwal
| Neural Networks and Deep Learning : A Textbook / Charu C. Aggarwal |
| Autore | Aggarwal, Charu C. |
| Edizione | [2. ed] |
| Pubbl/distr/stampa | Cham, : Springer, 2023 |
| Descrizione fisica | xxiv, 529 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] 82C32 - Neural nets applied to problems in time-dependent statistical mechanics [MSC 2020] 92B20 - Neural networks for/in biological studies, artificial life and related topics [MSC 2020] |
| Soggetto non controllato |
Adversarial learning
Artificial Intelligence Deep Learning Image Convolutional Networks Machine learning Neural networks Pre-Trained Language Models Recurrent Neural Networks Reinforcement Learning Transformers Unsupervised learning |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00278913 |
|
Aggarwal, Charu C.
|
||
| Cham, : Springer, 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Principles of Machine Learning : The Three Perspectives / Wenmin Wang
| Principles of Machine Learning : The Three Perspectives / Wenmin Wang |
| Autore | Wang, Wenmin |
| Pubbl/distr/stampa | Singapore, : Springer, 2024 |
| Descrizione fisica | xxxv, 527 p. : ill. ; 24 cm |
| Soggetto topico |
68-XX - Computer science [MSC 2020]
68Txx - Artificial intelligence [MSC 2020] |
| Soggetto non controllato |
Deep Learning
Machine learning Reinforcement Learning Supervised learning Unsupervised learning |
| ISBN | 978-98-19-75332-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00283794 |
|
Wang, Wenmin
|
||
| Singapore, : Springer, 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Statistical Mechanics of Neural Networks / Haiping Huang
| Statistical Mechanics of Neural Networks / Haiping Huang |
| Autore | Huang, Haiping |
| Pubbl/distr/stampa | Singapore, : Springer, : Higher Education, 2021 |
| Descrizione fisica | xviii, 296 p. : ill. ; 24 cm |
| Soggetto topico |
82-XX - Statistical mechanics, structure of matter [MSC 2020]
92B20 - Neural networks for/in biological studies, artificial life and related topics [MSC 2020] |
| Soggetto non controllato |
Cavity Method
Hopfield Model Mean field theory Random matrices Replica Method Restricted Boltzmann Machine Unsupervised learning |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00283198 |
|
Huang, Haiping
|
||
| Singapore, : Springer, : Higher Education, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||