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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
C++ Programming Fundamentals
C++ Programming Fundamentals
Autore Malhotra D
Edizione [1st ed.]
Pubbl/distr/stampa New York : , : Mercury Learning & Information, , 2022
Descrizione fisica 1 online resource (289 pages)
Disciplina 005.133
Altri autori (Persone) MalhotraN
Soggetto topico COMPUTERS / Programming Languages / C++
Soggetto non controllato AI
arrays
computer science
developers
embedded systems
file handling
game design
pointers
polymorphism
programming
video game
ISBN 1-68392-974-8
1-68392-975-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Title -- Copyright -- Contents -- Preface -- Acknowledgments -- Chapter 1 C++ and Beyond -- Introduction -- 1.1 The Origin of C++ -- 1.2 Why Use C++? -- 1.3 Various Programming Paradigms -- 1.3.1 Structural Programming -- 1.3.2 Procedural Programming -- 1.3.3 Object Oriented Programming -- 1.4 C++ Basics -- 1.4.1 Variables -- 1.4.2 Data Types -- 1.4.3 Data Modifiers -- 1.t C++ Execution Flow -- Summary -- Exercises -- Theory Questions -- MCQ-Based -- Practical Application -- References -- Books -- Websites -- Chapter 2 Basic Play in C++ -- 2.1 Literals, Constants, and Qualifiers -- 2.2 Stream-Based IO -- 2.3 Comments -- 2.4 Operators and Types -- 2.4.1 Types of Operators in C++ -- 2.5 Type Conversion -- 2.6 Keywords -- 2.7 Loops in C++ -- 2.9 Control Statements -- 2.9 Defining Functions -- 2.9.1 Why Use Functions? -- 2.10 C vs. C++ -- Summary -- Exercises -- Theory Questions -- MCQ-Based -- Practical Questions -- References -- Books -- Websites -- Chapter 3 Arrays and Strings -- 3.1 What is an Array? -- 3.1.1 Ways to Declare Arrays -- 3.1.2 Ways to Access Array Members -- 3.1.3 Traversing a 1D Array -- 3.2 Operations on an Array -- 3.2.1 Passing an Array to Functions -- 3.2.2 Finding the Length -- 3.2.3 Enum in C++ -- 3.2.4 Searching -- 3.3 Multi-Dimensional Array -- 3.4 Strings -- 3.5 String Functions -- Summary -- Exercises -- Theory Questions -- MCQ-Based -- Practical Questions -- References -- Books -- Websites -- Chapter 4 Pointers in C++ -- 4.1 Introduction -- 4.2 Pointers: Declaration and Initialization -- 4.3 Casting and Passing Pointers -- 4.3.1 Typecasting -- 4.3.2 Passing -- 4.4 Using Pointers with Arrays -- 4.5 Pointer Use -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 5 Classes in C++ -- 5.1 Class Making.
5.2 Constructors and Destructors -- 5.3 The This Pointer -- 5.4 Class Methods -- 5.5 The static Keyword -- 5.6 Memory Management and Garbage Collection in C++ -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 6 Inheritance -- 6.1 Introduction -- 6.2 Inheritance -- 6.2.1 Access Specifiers -- 6.2.2 Inheritance Modes -- 6.3 Types of Inheritance -- 6.4 Constructor Calling -- 6.5 Implementing Inheritance -- Summary -- Exercises -- Theory Questions -- Practial Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 7 Polymorphism -- 7.1 Introduction -- 7.2 Dynamic vs. Static Binding -- 7.3 Interface and Implementation -- 7.4 Function Overriding and Overloading -- 7.5 Friend and Generic Functions -- 7.5.1 Friend Functions -- 7.5.2 Generic Functions -- 7.6 Namespaces -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 8 Operator Overloading -- 8.1 Basics -- 8.2 How to Overload an Operator? -- 8.3 Overloading Unary Operators -- 8.4 Overloading Binary Operators -- 8.5 Overloading by Friend Function -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 9 Structure and Union -- 9.1 Structure: Declaration and Definition -- 9.2 Accessing a Structure -- 9.3 Union -- 9.4 Differences Between Structure and Union -- 9.5 Enum in C++ -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 10 Exception Handling -- 10.1 Errors and Exceptions -- 10.2 Exception Handling -- 10.3 Various Exceptions -- 10.4 Custom Exceptions in C++ -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Chapter 11 File Handling.
11.1 Files and Streams -- 11.2 File Operations -- 11.3 Random Access and Object Serialization -- Summary -- Exercises -- Theory Questions -- Practical Questions -- MCQ-Based -- References -- Books -- Websites -- Index.
Record Nr. UNINA-9910838375803321
Malhotra D  
New York : , : Mercury Learning & Information, , 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. 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
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. UNINA-9910586580203321
Shoham Sharon  
Cham, : Springer Nature, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Computer Science and Engineering Education for Pre-collegiate Students and Teachers
Computer Science and Engineering Education for Pre-collegiate Students and Teachers
Autore Burrows Andrea
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2019
Descrizione fisica 1 electronic resource (142 p.)
Soggetto non controllato secondary science
STEM outreach
mathematics (STEM) education
environmental radioactivity
learner analysis
coaching
learner-centered pedagogy
preservice teacher beliefs
computer science education
laboratory activity
science education
challenge-based learning
engineering
K–12 teacher
literature review
pre-collegiate teacher
scintillator detector
computing outreach
science
computer science application
pre-college engineering activities
K-12 teachers
engineering design process
?-ray spectroscopy
student engagement
in-situ measurements
conceptual assessment items
engineering education
Web-GIS platform
K–12
computer science
engineering outreach
online professional development training
pre-college STEM activities
Android app
students’ alternative conceptions
technology
inquiry-based science and technology
computer science integration
assessment tool
perceptions
pre-college computing activities
nuclear engineering experiment
conceptual change
NGSS
physics education
engineering design technology
ISBN 3-03897-941-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910346689903321
Burrows Andrea  
MDPI - Multidisciplinary Digital Publishing Institute, 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Data Science for IoT Engineers : A Systems Analytics Approach
Data Science for IoT Engineers : A Systems Analytics Approach
Autore Madhavan P. G
Pubbl/distr/stampa Bloomfield : , : Mercury Learning & Information, , 2021
Descrizione fisica 1 online resource (170 pages)
Disciplina 006.312024004678
Soggetto topico COMPUTERS / Desktop Applications / Presentation Software
Soggetto non controllato IOT
MATLAB
computer science
data analytics
engineering
mathematics
physics
ISBN 1-68392-640-4
1-68392-641-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Frontmatter -- Contents -- Preface -- About the Author -- PART I Machine Learning from Multiple Perspectives -- CHAPTER 1 Overview of Data Science -- CHAPTER 2 Introduction to Machine Learning -- CHAPTER 3 Systems Theory, Linear Algebra, and Analytics Basics -- CHAPTER 4 “Modern” Machine Learning -- PART II Systems Analytics -- CHAPTER 5 Systems Theory Foundations of Machine Learning -- CHAPTER 6 State Space Model and Bayes Filter -- CHAPTER 7 The Kalman Filter for Adaptive Machine Learning -- CHAPTER 8 The Need for Dynamical Machine Learning: The Bayesian Exact Recursive Estimation -- CHAPTER 9 Digital Twins -- Epilogue A New Random Field Theory -- Index
Record Nr. UNINA-9910795555703321
Madhavan P. G  
Bloomfield : , : Mercury Learning & Information, , 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Data Science for IoT Engineers : A Systems Analytics Approach
Data Science for IoT Engineers : A Systems Analytics Approach
Autore Madhavan P. G
Pubbl/distr/stampa Bloomfield : , : Mercury Learning & Information, , 2021
Descrizione fisica 1 online resource (170 pages)
Disciplina 006.312024004678
Soggetto topico COMPUTERS / Desktop Applications / Presentation Software
Soggetto non controllato IOT
MATLAB
computer science
data analytics
engineering
mathematics
physics
ISBN 1-68392-640-4
1-68392-641-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Frontmatter -- Contents -- Preface -- About the Author -- PART I Machine Learning from Multiple Perspectives -- CHAPTER 1 Overview of Data Science -- CHAPTER 2 Introduction to Machine Learning -- CHAPTER 3 Systems Theory, Linear Algebra, and Analytics Basics -- CHAPTER 4 “Modern” Machine Learning -- PART II Systems Analytics -- CHAPTER 5 Systems Theory Foundations of Machine Learning -- CHAPTER 6 State Space Model and Bayes Filter -- CHAPTER 7 The Kalman Filter for Adaptive Machine Learning -- CHAPTER 8 The Need for Dynamical Machine Learning: The Bayesian Exact Recursive Estimation -- CHAPTER 9 Digital Twins -- Epilogue A New Random Field Theory -- Index
Record Nr. UNINA-9910810050903321
Madhavan P. G  
Bloomfield : , : Mercury Learning & Information, , 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui