top

  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.

  Info

  • Utilizzare questo link per rimuovere la selezione effettuata.
Advances in Artificial Intelligence: Models, Optimization, and Machine Learning
Advances in Artificial Intelligence: Models, Optimization, and Machine Learning
Autore Leon Florin
Pubbl/distr/stampa Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica 1 electronic resource (362 p.)
Soggetto topico Research & information: general
Mathematics & science
Soggetto non controllato large margin nearest neighbor regression
distance metrics
prototypes
evolutionary algorithm
approximate differential optimization
multiple point hill climbing
adaptive sampling
free radical polymerization
autonomous driving
object tracking
trajectory prediction
deep neural networks
stochastic methods
applied machine learning
classification and regression
data mining
ensemble model
engineering informatics
gender-based violence in Mexico
twitter messages
class imbalance
k-nearest neighbor
instance-based learning
graph neural network
deep learning
hyperparameters
machine learning
optimization
inference
metaheuristics
animal-inspired
exploration
exploitation
hot rolled strip steel
surface defects
defect classification
knockout tournament
dynamic programming algorithm
computational complexity
combinatorics
intelligent transport systems
traffic control
spatial-temporal variable speed limit
multi-agent systems
reinforcement learning
distributed W-learning
urban motorways
multi-agent framework
NET framework
simulations
agent-based systems
agent algorithms
software design
multisensory fingerprint
interoperability
DeepFKTNet
classification
generative adversarial networks
image classification
transfer learning
plastic bottle
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti Advances in Artificial Intelligence
Record Nr. UNINA-9910580212403321
Leon Florin  
Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Automated Deduction - CADE 28 [[electronic resource] ] : 28th International Conference on Automated Deduction, Virtual Event, July 12-15, 2021, Proceedings
Automated Deduction - CADE 28 [[electronic resource] ] : 28th International Conference on Automated Deduction, Virtual Event, July 12-15, 2021, Proceedings
Autore Platzer André
Pubbl/distr/stampa Cham, : Springer International Publishing AG, 2021
Descrizione fisica 1 online resource (655 p.)
Altri autori (Persone) SutcliffeGeoff
Collana Lecture Notes in Computer Science
Soggetto topico Artificial intelligence
Mathematical theory of computation
Computer programming / software development
Software Engineering
Soggetto non controllato Artificial Intelligence
Mathematical Logic and Formal Languages
Logics and Meanings of Programs
Software Engineering
Formal Languages and Automata Theory
Computer Science Logic and Foundations of Programming
automata theory
boolean functions
computer programming
first order logic
formal languages
formal logic
logic programming
model checking
program verification
semantics
software architecture
software design
software quality
software verification
theorem provers
theorem proving
Mathematical theory of computation
Computer programming / software engineering
Computer architecture & logic design
ISBN 3-030-79876-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti Automated Deduction – CADE 28
Automated Deduction - CADE 28
Record Nr. UNINA-9910491025703321
Platzer André  
Cham, : Springer International Publishing AG, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Automated Deduction - CADE 28 [[electronic resource] ] : 28th International Conference on Automated Deduction, Virtual Event, July 12-15, 2021, Proceedings
Automated Deduction - CADE 28 [[electronic resource] ] : 28th International Conference on Automated Deduction, Virtual Event, July 12-15, 2021, Proceedings
Autore Platzer André
Pubbl/distr/stampa Cham, : Springer International Publishing AG, 2021
Descrizione fisica 1 online resource (655 p.)
Altri autori (Persone) SutcliffeGeoff
Collana Lecture Notes in Computer Science
Soggetto topico Artificial intelligence
Mathematical theory of computation
Computer programming / software development
Software Engineering
Soggetto non controllato Artificial Intelligence
Mathematical Logic and Formal Languages
Logics and Meanings of Programs
Software Engineering
Formal Languages and Automata Theory
Computer Science Logic and Foundations of Programming
automata theory
boolean functions
computer programming
first order logic
formal languages
formal logic
logic programming
model checking
program verification
semantics
software architecture
software design
software quality
software verification
theorem provers
theorem proving
Mathematical theory of computation
Computer programming / software engineering
Computer architecture & logic design
ISBN 3-030-79876-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti Automated Deduction – CADE 28
Automated Deduction - CADE 28
Record Nr. UNISA-996464423903316
Platzer André  
Cham, : Springer International Publishing AG, 2021
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Automated reasoning : 11th International Joint Conference, IJCAR 2022, Haifa, Israel, August 8-10, 2022, Proceedings / / editors, Jasmin Blanchette, Laura Kovács, Dirk Pattinson
Automated reasoning : 11th International Joint Conference, IJCAR 2022, Haifa, Israel, August 8-10, 2022, Proceedings / / editors, Jasmin Blanchette, Laura Kovács, Dirk Pattinson
Autore Blanchette Jasmin
Pubbl/distr/stampa Cham, : Springer Nature, 2022
Descrizione fisica 1 online resource (xv, 756 pages) : illustrations (some color)
Disciplina 006.333
Altri autori (Persone) BlanchetteJasmin
KovácsLaura
PattinsonDirk <1970->
Collana Lecture notes in computer science
Soggetto topico Automatic theorem proving
Computer logic
Soggetto non controllato artificial intelligence
automata theory
computer hardware
computer networks
computer programming
computer systems
embedded systems
formal languages
formal logic
logic programming
network protocols
semantics
software architecture
software design
software engineering
theoretical computer science
ISBN 3-031-10769-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910585785003321
Blanchette Jasmin  
Cham, : Springer Nature, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Automated reasoning : 11th International Joint Conference, IJCAR 2022, Haifa, Israel, August 8-10, 2022, Proceedings / / editors, Jasmin Blanchette, Laura Kovács, Dirk Pattinson
Automated reasoning : 11th International Joint Conference, IJCAR 2022, Haifa, Israel, August 8-10, 2022, Proceedings / / editors, Jasmin Blanchette, Laura Kovács, Dirk Pattinson
Autore Blanchette Jasmin
Pubbl/distr/stampa Cham, : Springer Nature, 2022
Descrizione fisica 1 online resource (xv, 756 pages) : illustrations (some color)
Disciplina 006.333
Altri autori (Persone) BlanchetteJasmin
KovácsLaura
PattinsonDirk <1970->
Collana Lecture notes in computer science
Soggetto topico Automatic theorem proving
Computer logic
Soggetto non controllato artificial intelligence
automata theory
computer hardware
computer networks
computer programming
computer systems
embedded systems
formal languages
formal logic
logic programming
network protocols
semantics
software architecture
software design
software engineering
theoretical computer science
ISBN 3-031-10769-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996483156703316
Blanchette Jasmin  
Cham, : Springer Nature, 2022
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I / / edited by Alessandro Crimi, Spyridon Bakas
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I / / edited by Alessandro Crimi, Spyridon Bakas
Autore Crimi Alessandro
Edizione [1st ed. 2022.]
Pubbl/distr/stampa Cham, : Springer Nature, 2022
Descrizione fisica 1 online resource (XXI, 489 p. 171 illus., 134 illus. in color.)
Disciplina 006.37
Collana Lecture Notes in Computer Science
Soggetto topico Computer vision
Artificial intelligence
Computer engineering
Computer networks
Application software
Computer Vision
Artificial Intelligence
Computer Engineering and Networks
Computer and Information Systems Applications
Soggetto non controllato artificial intelligence
bioinformatics
computer science
computer systems
computer vision
education
image analysis
image processing
image segmentation
learning
machine learning
medical images
neural networks
pattern recognition
segmentation methods
software design
software engineering
software quality
validation
verification and validation
ISBN 3-031-08999-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Supervoxel Merging towards Brain Tumor Segmentation -- Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRI -- Modeling multi-annotator uncertainty as multi-class segmentation problem -- Modeling multi-annotator uncertainty as multi-class segmentation problem -- Adaptive unsupervised learning with enhanced feature representation for intra-tumor partitioning and survival prediction for glioblastoma -- Predicting isocitrate dehydrogenase mutation status in glioma using structural brain networks and graph neural networks -- Optimization of Deep Learning based Brain Extraction in MRI for Low Resource Environments. Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task -- Unet3D with Multiple Atrous Convolutions Attention Block for Brain Tumor Segmentation -- BRATS2021: exploring each sequence in multi-modal input for baseline U-net performance -- Automatic Brain Tumor Segmentation using Multi-scale Features and Attention Mechanism -- Simple and Fast Convolutional Neural Network applied to median cross sections for predicting the presence of MGMT promoter methylation in FLAIR MRI scans -- MSViT: Multi Scale Vision Transformer forBiomedical Image Segmentation -- Unsupervised Multimodal -- HarDNet-BTS: A Harmonic Shortcut Network for Brain Tumor Segmentation -- Multimodal Brain Tumor Segmentation Algorithm -- Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images -- Multi-plane UNet++ Ensemble for Glioblastoma Segmentation -- Multimodal Brain Tumor Segmentation using Modified UNet Architecture -- A video data based transfer learning approach for classification of MGMT status in brain tumor MR images -- Multimodal Brain Tumor Segmentation Using a 3D ResUNet in BraTS 2021 -- 3D MRI brain tumour segmentation with autoencoder regularization and Hausdorff distance loss function -- 3D CMM-Net with Deeper Encoder for Semantic Segmentation of Brain Tumors in BraTS2021 Challenge -- Cascaded training pipeline for 3D brain tumor segmentation -- nnU-Net with Region-based Training and Loss Ensembles for Brain Tumor Segmentation -- Brain Tumor Segmentation Using Attention Activated U-Net with Positive Mining -- Automatic segmentation of brain tumor using 3D convolutional neural networks -- Hierarchical and Global Modality Interaction for Brain Tumor Segmentation -- Ensemble Outperforms Single Models in Brain Tumor Segmentation -- Brain Tumor Segmentation using UNet-Context Encoding Network -- Ensemble CNN Networks for GBM Tumors Segmentation using Multi-parametric MRI.
Record Nr. UNINA-9910585786203321
Crimi Alessandro  
Cham, : Springer Nature, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I / / edited by Alessandro Crimi, Spyridon Bakas
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I / / edited by Alessandro Crimi, Spyridon Bakas
Autore Crimi Alessandro
Edizione [1st ed. 2022.]
Pubbl/distr/stampa Cham, : Springer Nature, 2022
Descrizione fisica 1 online resource (XXI, 489 p. 171 illus., 134 illus. in color.)
Disciplina 006.37
Collana Lecture Notes in Computer Science
Soggetto topico Computer vision
Artificial intelligence
Computer engineering
Computer networks
Application software
Computer Vision
Artificial Intelligence
Computer Engineering and Networks
Computer and Information Systems Applications
Soggetto non controllato artificial intelligence
bioinformatics
computer science
computer systems
computer vision
education
image analysis
image processing
image segmentation
learning
machine learning
medical images
neural networks
pattern recognition
segmentation methods
software design
software engineering
software quality
validation
verification and validation
ISBN 3-031-08999-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Supervoxel Merging towards Brain Tumor Segmentation -- Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRI -- Modeling multi-annotator uncertainty as multi-class segmentation problem -- Modeling multi-annotator uncertainty as multi-class segmentation problem -- Adaptive unsupervised learning with enhanced feature representation for intra-tumor partitioning and survival prediction for glioblastoma -- Predicting isocitrate dehydrogenase mutation status in glioma using structural brain networks and graph neural networks -- Optimization of Deep Learning based Brain Extraction in MRI for Low Resource Environments. Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task -- Unet3D with Multiple Atrous Convolutions Attention Block for Brain Tumor Segmentation -- BRATS2021: exploring each sequence in multi-modal input for baseline U-net performance -- Automatic Brain Tumor Segmentation using Multi-scale Features and Attention Mechanism -- Simple and Fast Convolutional Neural Network applied to median cross sections for predicting the presence of MGMT promoter methylation in FLAIR MRI scans -- MSViT: Multi Scale Vision Transformer forBiomedical Image Segmentation -- Unsupervised Multimodal -- HarDNet-BTS: A Harmonic Shortcut Network for Brain Tumor Segmentation -- Multimodal Brain Tumor Segmentation Algorithm -- Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images -- Multi-plane UNet++ Ensemble for Glioblastoma Segmentation -- Multimodal Brain Tumor Segmentation using Modified UNet Architecture -- A video data based transfer learning approach for classification of MGMT status in brain tumor MR images -- Multimodal Brain Tumor Segmentation Using a 3D ResUNet in BraTS 2021 -- 3D MRI brain tumour segmentation with autoencoder regularization and Hausdorff distance loss function -- 3D CMM-Net with Deeper Encoder for Semantic Segmentation of Brain Tumors in BraTS2021 Challenge -- Cascaded training pipeline for 3D brain tumor segmentation -- nnU-Net with Region-based Training and Loss Ensembles for Brain Tumor Segmentation -- Brain Tumor Segmentation Using Attention Activated U-Net with Positive Mining -- Automatic segmentation of brain tumor using 3D convolutional neural networks -- Hierarchical and Global Modality Interaction for Brain Tumor Segmentation -- Ensemble Outperforms Single Models in Brain Tumor Segmentation -- Brain Tumor Segmentation using UNet-Context Encoding Network -- Ensemble CNN Networks for GBM Tumors Segmentation using Multi-parametric MRI.
Record Nr. UNISA-996483157303316
Crimi Alessandro  
Cham, : Springer Nature, 2022
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Computer aided verification : 34th International Conference, CAV 2022, Haifa, Israel, August 7-10, 2022, proceedings . Part II. / / editors, Sharon Shoham, Yakir Vizel
Computer aided verification : 34th International Conference, CAV 2022, Haifa, Israel, August 7-10, 2022, proceedings . Part II. / / editors, Sharon Shoham, Yakir Vizel
Autore Shoham Sharon
Pubbl/distr/stampa Cham, : Springer Nature, 2022
Descrizione fisica 1 online resource (560 pages) : illustrations (black and white)
Altri autori (Persone) VizelYakir
Collana Lecture notes in computer science
Soggetto topico Computer software - Verification
Soggetto non controllato architecting
architecture verification and validation
artificial intelligence
computer programming
computer science
computer systems
databases
distributed computer systems
embedded systems
engineering
formal languages
formal logic
linguistics
mathematics
model checking
software architecture
software design
software engineering
software quality
theoretical computer science
ISBN 3-031-13188-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910586580503321
Shoham Sharon  
Cham, : Springer Nature, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Computer aided verification : 34th International Conference, CAV 2022, Haifa, Israel, August 7-10, 2022, proceedings . Part II. / / editors, Sharon Shoham, Yakir Vizel
Computer aided verification : 34th International Conference, CAV 2022, Haifa, Israel, August 7-10, 2022, proceedings . Part II. / / editors, Sharon Shoham, Yakir Vizel
Autore Shoham Sharon
Pubbl/distr/stampa Cham, : Springer Nature, 2022
Descrizione fisica 1 online resource (560 pages) : illustrations (black and white)
Altri autori (Persone) VizelYakir
Collana Lecture notes in computer science
Soggetto topico Computer software - Verification
Soggetto non controllato architecting
architecture verification and validation
artificial intelligence
computer programming
computer science
computer systems
databases
distributed computer systems
embedded systems
engineering
formal languages
formal logic
linguistics
mathematics
model checking
software architecture
software design
software engineering
software quality
theoretical computer science
ISBN 3-031-13188-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996485664103316
Shoham Sharon  
Cham, : Springer Nature, 2022
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Computer aided verification : 34th International Conference, CAV 2022, Haifa, Israel, August 7-10, 2022, proceedings . Part I. / / editors, Sharon Shoham, Yakir Vizel
Computer aided verification : 34th International Conference, CAV 2022, Haifa, Israel, August 7-10, 2022, proceedings . Part I. / / editors, Sharon Shoham, Yakir Vizel
Autore Shoham Sharon
Pubbl/distr/stampa Cham, : Springer Nature, 2022
Descrizione fisica 1 online resource (563 pages) : illustrations (black and white)
Disciplina 005.14
Collana Lecture Notes in Computer Science
Soggetto topico Computer software - Verification
Soggetto non controllato architecting
architecture verification and validation
artificial intelligence
computer programming
computer science
computer systems
distributed computer systems
distributed systems
embedded systems
formal logic
mathematics
model checking
programming languages
software architecture
software design
software engineering
software quality
theoretical computer science
verification
verification and validation
ISBN 3-031-13185-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996485664203316
Shoham Sharon  
Cham, : Springer Nature, 2022
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui