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- Ciaburro, Giuseppe, author.
- Birmingham, UK : Packt Publishing, 2017.
- Description
- Book — 1 online resource (1 volume) : illustrations
- Summary
-
Extract patterns and knowledge from your data in easy way using MATLAB About This Book * Get your first steps into machine learning with the help of this easy-to-follow guide * Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB * Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well. What You Will Learn * Learn the introductory concepts of machine learning. * Discover different ways to transform data using SAS XPORT, import and export tools, * Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. * Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. * Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. * Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. * Learn feature selection and extraction for dimensionality reduction leading to improved performance. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You'll start by getting your system ready with t he MATLAB environment for machine learning and you'll see how to easily interact with the Matlab workspace. We'll then move on to data cleansing, mining and analyzing various data types in machine learning and you'll see how to display data values on a plot. Next, you'll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You'll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you'll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Style and approach The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.
(source: Nielsen Book Data)
- Ciaburro, Giuseppe, author.
- Birmingham, UK : Packt Publishing, 2017.
- Description
- Book — 1 online resource (1 volume) : illustrations
- Summary
-
Extract patterns and knowledge from your data in easy way using MATLAB About This Book * Get your first steps into machine learning with the help of this easy-to-follow guide * Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB * Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well. What You Will Learn * Learn the introductory concepts of machine learning. * Discover different ways to transform data using SAS XPORT, import and export tools, * Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. * Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. * Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. * Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. * Learn feature selection and extraction for dimensionality reduction leading to improved performance. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You'll start by getting your system ready with t he MATLAB environment for machine learning and you'll see how to easily interact with the Matlab workspace. We'll then move on to data cleansing, mining and analyzing various data types in machine learning and you'll see how to display data values on a plot. Next, you'll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You'll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you'll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Style and approach The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.
(source: Nielsen Book Data)
- A2IA (Conference) (1st : 2020 : Meknes, Morocco)
- Cham : Springer, [2021]
- Description
- Book — 1 online resource Digital: text file.PDF.
- Summary
-
- A Study of Energy Reduction Strategies in Renewable Hybrid Grid.- Classification and Watermarking of Brain Tumor using Artificial and Convolutional Neural Networks.- A Proposal for a Deep Learning Model to Enhance Student Guidance and Reduce Dropout.- EduBot: An Unsupervised Domain-Specific Chatbot for Educational Institutions.- SQL Generation from Natural Language using Supervised Learning and Recurrent Neural Networks.- Toward Intelligent Solution to Identify Learner Attitude from Source Code.
- (source: Nielsen Book Data)
(source: Nielsen Book Data)
- Cham, Switzerland : Springer, [2021]
- Description
- Book — 1 online resource
- Summary
-
- A Fuzzy Ontology Based Approach To Support Product Eco-Design.-
- A Genetic-based SVM Approach for Quality Data Classification.- Towards a platform to implement an intelligent and predictive maintenance in the context of industry.- Towards a Prediction Analysis in an Industrial Context.- Methodology for Implementation of Industry . Technologies in Supply Chain for SMEs.- A Deep Reinforcement Learning DRL Decision Model For Heating Process Parameters Identification In Automotive Glass Manufacturing
- Analytic Hierarchy Process AHP for supply chain . risks management.- SmartDFRelevance: a Holonic Agent based System for Engineering Industrial Projects in Concurrent Engineering Context.- A Cyber-Physical Warehouse Management System Architecture in an.- Industry . context.- PLM and Smart technologies for product and supply chain design.- Production systems simulation considering Non-Productive Times and Human Factors.- Distributed and Embedded System to Control Traffic Collision Based on Artificial Intelligence.- The Emergence and Decision Support in Complex System with Fuzzy Logic Control.- Markov Decision Processes with Discounted Costs over a Finite Horizon: Action Elimination.- Robust adaptive fuzzy path tracking control of Differential Wheeled Mobile Robot.- Deep Learning approach for Automated Guided Vehicle System.- Path Planning Using Particle Swarm Optimization And Fuzzy Logic
- Prediction of Robot localization states using Hidden Markov Models.- A New Approach for Multi-Agent Reinforcement Learning.- Recommender System for Most Relevant k Pick-Up Points.- Feature Detection and Tracking for Visual Effects: Augmented Reality and Video Stabilization.- Spectral image recognition using artificial dynamic neural network in information resonance mode.- U-Net Based Model for Obfuscated Human Faces Reconstruction.- A Machine Learning Assistant for Choosing Operators and Tuning Their Parameters in Image Processing Tasks.- Convergence and parameters setting of continuous Hopfield neural networks applied to image restoration problem.- The Ibn Battouta Air Traffic Control Corpus with Real Life ADS-B and METAR data.- Weed Recognition System For Low-Land Rice Precision Farming Using Deep Learning Approach.- A Comparative Study Between Mixture and Stepwise Regression to Model The Parameters Of The Composting Process.- Deep Learning Based Sponge Gourd Diseases Recognition For Commercial Cultivation in Bangladesh.- Exploitation of vegetation indices and Random Forest for cartography of rosemary cover: application to Gourrama region, Morocco.
- (source: Nielsen Book Data)
(source: Nielsen Book Data)
- Cham : Springer, 2020.
- Description
- Book — 1 online resource (464 pages)
- Summary
-
- 1. Introduction.-
- 2. Machine Learning Methods for Spatial and Temporal Parameter Estimation.-
- 3. Deep Learning for Hyperspectral Image Analysis, Part I: Theory and Algorithms.-
- 4. Deep Learning for Hyperspectral Image Analysis, Part II: Applications to Remote Sensing and Biomedicine.-
- 5. Advances in Deep Learning for Hyperspectral Image Analysis - Addressing Challenges Arising in Practical Imaging Scenarios.-
- 6. Addressing the Inevitable Imprecision: Multiple Instance Learning for Hyperspectral Image Analysis.-
- 7. Supervised, Semi Supervised and Unsupervised Learning for Hyperspectral Regression.-
- 8. Sparsity-based Methods for Classification.-
- 9. Multiple Kernel Learning for Hyperspectral Image Classification.-
- 10. Low Dimensional Manifold Model in Hyperspectral Image Reconstruction.-
- 11. Deep Sprase Band Selection for Hyperspectral Face Recognition.-
- 12. Detection of Large-Scale and Anomalous Changes.-
- 13. Recent Advances in Hyperspectral Unmixing Using Sparse Techniques and Deep Learning.-
- 14. Chapter Hyperspectral-Multispectral Image Fusion Enhancement Based on Deep Learning.-
- 15. Automatic Target Detection for Sparse Hyperspectral Images.
- (source: Nielsen Book Data)
(source: Nielsen Book Data)
6. Designing sociable robots [2002]
- Breazeal, Cynthia L.
- Cambridge, Mass. : MIT Press, ©2002.
- Description
- Book — 1 online resource (xviii, 263 pages) : illustrations
- Summary
-
- 1. The vision of sociable robots
- 2. Robot in society: a question of interface
- 3. Insights from developmental psychology
- 4. Designing sociable robots
- 5. The physical robot
- 6. The vision system
- 7. The auditory system
- 8. The motivation system
- 9. The behavior system
- 10. Facial animation and expression
- 11. Expressive vocalization system
- 12. Social constraints on animate vision
- 13. Grand challenges of building sociable robots.
(source: Nielsen Book Data)
- Cham, Switzerland : Springer, [2020]
- Description
- Book — 1 online resource
- Summary
-
- 1. A Comprehensive Introduction to Photometric 3D-Reconstruction.-
- 2. Perspective Shape from Shading an Exposition on Recent Works with New Experiments.-
- 3. RGBD-Fusion: Depth Refinement for Diffuse and Specular Objects.-
- 4. Non-Rigid Structure from Motion and Shading.-
- 5. On the Well-Posedness of Uncalibrated Photometric Stereo Under General Lighting.-
- 6. Recent Progress in Shape from Polarization.-
- 7. Estimating Facial Aging using Light Scattering Photometry.
- (source: Nielsen Book Data)
(source: Nielsen Book Data)
- ICVS (Conference : Computer vision systems) (10th : 2015 : Copenhagen, Denmark)
- Cham : Springer, 2015.
- Description
- Book — 1 online resource (xv, 544 pages) : illustrations Digital: text file.PDF.
- Summary
-
- Biological and cognitive vision
- Hardware-implemented and real-time vision systems
- High-level vision
- Learning and adaptation
- Robot vision.- Vision systems applications.
- IbPRIA (Conference) (7th : 2015 : Santiago de Compostela, Spain)
- Cham : Springer, 2015.
- Description
- Book — 1 online resource (xvi, 753 pages) : illustrations Digital: text file.PDF.
- Summary
-
- Pattern Recognition and Machine Learning
- Spatiotemporal Stacked Sequential Learning for Pedestrian Detection
- Social Signaling Descriptor for Group Behaviour Analysis
- A New Smoothing Method for Lexicon-Based Handwritten Text Keyword Spotting
- Empirical Evaluation of Different Feature Representations for Social Circles Detection
- Source-Target-Source Classification Using Stacked Denoising Autoencoders
- On the Impact of Distance Metrics in Instance-Based Learning Algorithms
- Multi-class Boosting for Imbalanced Data
- Computer Vision
- Object Discovery Using CNN Features in Egocentric Videos
- Prototype Generation on Structural Data Using Dissimilarity Space Representation: A Case of Study
- Estimation and Tracking of Partial Planar Templates to Improve VSLAM
- Human Centered Scene Understanding Based on 3D Long-Term Tracking Data
- Fast Head Pose Estimation for Human-Computer Interaction
- Structured Light System Calibration for Perception in Underwater Tanks
- Dense 3D SLAM in Dynamic Scenes Using Kinect
- Scene Recognition Invariant to Symmetrical Reflections and Illumination Conditions in Robotics
- System for Medical Mask Detection in the Operating Room Through Facial Attributes
- Image and Signal Processing
- New Method for Obtaining Optimal Polygonal Approximations
- Noise Decomposition Using Polynomial Approximation
- Color Correction for Image Stitching by Monotone Cubic Spline Interpolation
- Structured Output Prediction with Hierarchical Loss Functions for Seafloor Imagery Taxonomic Categorization
- Escaping Path Approach with Extended Neighborhood for Speckle Noise Reduction
- Adaptive Line Matching for Low-Textured Images
- Unsupervised Approximation of Digital Planar Curves
- On the Modification of Binarization Algorithms to Retain Grayscale Information for Handwritten Text Recognition
- Applications
- Improving the Minimum Description Length Inference of Phrase-Based Translation Models
- A Kinect-Based System to Assess Lymphedema Impairments in Breast Cancer Patients
- Arabic Writer Identification Using Local Binary Patterns (LBP) of Handwritten Fragments
- A Fuzzy C-Means Algorithm for Fingerprint Segmentation
- Word-Graph Based Applications for Handwriting Documents: Impact of Word-Graph Size on Their Performances
- Temporal Segmentation of Digital Colposcopies
- Goal-Driven Phenotyping Through Spectral Imaging for Grape Aromatic Ripeness Assessment
- Medical Image
- Robust 3D Active Shape Model for the Segmentation of the Left Ventricle in MRI
- Kernel-Based Feature Relevance Analysis for ECG Beat Classification
- Spatial-Dependent Similarity Metric Supporting Multi-atlas MRI Segmentation
- Color Detection in Dermoscopy Images Based on Scarce Annotations
- Pattern Recognition and Machine Learning
- Spectral Clustering Using Friendship Path Similarity
- R-Clustering for Egocentric Video Segmentation
- Applying Basic Features from Sentiment Analysis for Automatic Irony Detection
- Exploiting the Bin-Class Histograms for Feature Selection on Discrete Data
- Time-Series Prediction Based on Kernel Adaptive Filtering with Cyclostationary Codebooks
- Latent Topic Encoding for Content-Based Retrieval
- Dissimilarity-Based Learning from Imbalanced Data with Small Disjuncts and Noise
- Binary and Multi-class Parkinsonian Disorders Classification Using Support Vector Machines
- Peripheral Nerve Segmentation Using Speckle Removal and Bayesian Shape Models
- Measuring Scene Detection Performance
- Threshold of Graph-Based Volumetric Segmentation
- Brain Neural Data Analysis with Feature Space Defined by Descriptive Statistics
- Extremely Overlapping Vehicle Counting
- Sentence Clustering Using Continuous Vector Space Representation
- Online Learning of Stochastic Bi-automaton to Model Dialogues
- Single-Channel Separation Between Stationary and Non-stationary Signals Using Relevant Information
- Computer Vision
- A New Trajectory Based Motion Segmentation Benchmark Dataset (UdG-MS15)
- Escritoire: A Multi-touch Desk with e-Pen Input for Capture, Management and Multimodal Interactive Transcription of Handwritten Documents
- Person Enrollment by Face-Gait Fusion
- Homographic Class Template for Logo Localization and Recognition
- Multimodal Object Recognition Using Random Clustering Trees
- Videogrammetry System for Wind Turbine Vibration Monitoring
- Canonical Views for Scene Recognition in Mobile Robotics
- Crater Detection in Multi-ring Basins of Mercury
- Iterative Versus Voting Method to Reach Consensus Given Multiple Correspondences of Two Sets
- Extracting Categories by Hierarchical Clustering Using Global Relational Features
- A Calibration Algorithm for Multi-camera Visual Surveillance Systems Based on Single-View Metrology
- 3D-Guided Multiscale Sliding Window for Pedestrian Detection
- A Feature-Based Gaze Estimation Algorithm for Natural Light Scenarios
- Image and Signal Processing
- Fast Simple Linear Iterative Clustering by Early Candidate Cluster Elimination
- Pectoral Muscle Segmentation in Mammograms Based on Cartoon-Texture Decomposition
- PPG Beat Reconstruction Based on Shape Models and Probabilistic Templates for Signals Acquired with Conventional Smartphones
- Peripheral Nerves Segmentation in Ultrasound Images Using Non-linear Wavelets and Gaussian Processes
- Improving Diffusion Tensor Estimation Using Adaptive and Optimized Filtering Based on Local Similarity
- Dimension Reduction of Hyperspectral Image with Rare Event Preserving
- Applications
- Clustering of Strokes from Pen-Based Music Notation: An Experimental Study
- Image Analysis-Based Automatic Detection of Transmission Towers Using Aerial Imagery
- A Sliding Window Framework for Word Spotting Based on Word Attributes
- Combining Statistical and Semantic Knowledge for Sarcasm Detection in Online Dialogues
- Estimating Fuel Consumption from GPS Data
- A Bag-of-phonemes Model for Homeplace Classification of Mandarin Speakers
- A Gaussian Process Emulator for Estimating the Volume of Tissue Activated During Deep Brain Stimulation
- Genetic Seam Carving: A Genetic Algorithm Approach for Content-Aware Image Retargeting
- Analysis of Expressiveness of Portuguese Sign Language Speakers
- Automatic Eye Localization; Multi-block LBP vs. Pyramidal LBP Three-Levels Image Decomposition for Eye Visual Appearance Description
- Clinical Evaluation of an Automatic Method for Segmentation and Characterization of the Thoracic Aorta with and Without Aneurysm Patients
- Combined MPEG7 Color Descriptors for Image Classification: Bypassing the Training Phase
- A Multi-platform Graphical Software for Determining Reproductive Parameters in Fishes Using Histological Image Analysis.
- EMMCVPR (Conference) (11th : 2017 : Venice, Italy)
- Cham, Switzerland : Springer, 2018.
- Description
- Book — 1 online resource (xii, 582 pages) Digital: text file.PDF.
- Summary
-
- Clustering and Quantum Methods.- Motion and Tracking.- Image Processing and Segmentation.- Color, Shading and Reflectance of Light.- Propagation and Time-evolution.- Inference, Labeling, and Relaxation.
- (source: Nielsen Book Data)
(source: Nielsen Book Data)
- International Workshop on Combinatorial Image Analysis (18th : 2017 : Plovdiv, Bulgaria)
- Cham, Switzerland : Springer, 2017.
- Description
- Book — 1 online resource (xv, 357 pages) : illustrations Digital: text file.PDF.
- Summary
-
- Discrete geometry and topology.- Tilings and patterns.- Grammars, models and other technical tools for image analysis.- Image segmentation.- Classification.- Reconstruction.- Compression.- Texture analysis.-Bioimaging.
- (source: Nielsen Book Data)
(source: Nielsen Book Data)
- IbPRIA (Conference) (8th : 2017 : Faro, Portugal)
- Cham, Switzerland : Springer, [2017]
- Description
- Book — 1 online resource (XVI, 549 pages) : illustrations Digital: text file.PDF.
- Summary
-
- Pattern Recognition and Machine Learning.- Computer Vision.- Image and Signal Processing.- Medical Image.-Applications.
- (source: Nielsen Book Data)
(source: Nielsen Book Data)
- IGTA (Conference) (11th : 2016 : Beijing, China)
- Singapore : Springer, 2016.
- Description
- Book — 1 online resource (xiii, 246 pages) : illustrations
- Summary
-
- Image processing technology
- Image analysis and understanding
- Computer vision and pattern recognition
- Big data mining, computer graphics and VR.-Image technology application.
- International Workshop on Combinatorial Image Analysis (17th : 2015 : Kolkata, India)
- Cham : Springer, 2015.
- Description
- Book — 1 online resource (xiii, 363 pages) : illustrations Digital: text file.PDF.
- Summary
-
- Intro
- Preface
- Organization
- Contents
- Invited Talk
- Digital Analytical Geometry: How Do I Define a Digital Analytical Object?
- 1 Introduction
- 2 Digitization
- 2.1 Notations
- 2.2 General Remarks on Digitizations
- 2.3 Morphological Digitizations
- 3 Analytical Characterization of Digital Objects
- 3.1 Direct Defined Analytical Digital Objects
- 3.2 Digitized Analytical Objects
- 4 Conclusion and Perspectives
- References
- Theoretical Foundations of Combinatorial Image Analysis
- Digital Geometry and Topology
- Fuzzy Connectedness Segmentation: A Brief Presentation of the Literature
- 1 Introduction
- 2 Basic Definitions
- 3 A Simple Multi Object Fuzzy Segmentation (MOFS) Algorithm
- 4 Robustness of Fuzzy Connectedness Segmentations
- 5 Unified Theory of FC Segmentations
- 6 Conclusion
- References
- Equivalent Sequential and Parallel Subiteration-Based Surface-Thinning Algorithms
- 1 Introduction
- 2 Basic Notions and Results
- 3 Parallel and Sequential 6-Subiteration Surface-Thinning Algorithms
- 4 Verification
- 5 Conclusions
- References
- Relative Convex Hull Determination from Convex Hulls in the Plane
- 1 Introduction
- 2 Preliminaries
- 3 Definition and Properties of the Relative Convex Hull
- 4 Previous Algorithms of Determining the Relative Convex Hull for Simple Polygons in the Plane
- 5 A New Algorithm of Determining the Relative Convex Hull for Simple Polygons in the Plane
- 5.1 Vertex Lists, Convex Hull Determination and Cavity Detection
- 5.2 Processing of One Cavity
- 5.3 Detection and Processing of Subsequent Cavities
- 5.4 Pseudocode, Implementation, and Complexity
- 6 Conclusion and Future Work
- On the Connectivity and Smoothness of Discrete Spherical Circles
- 1 Introduction
- 1.1 Motivation
- 1.2 Definitions and Terminologies
- 2 Discrete Spheres, Types, Ordering
- 3 Discrete Spherical Circles
- 3.1 Discretization Classes
- 3.2 Smoothness of Spherical Circles
- 3.3 Algorithm for Discrete Spherical Circle
- 4 Results and Discussion
- References
- Optimal Consensus Set for nD Fixed Width Annulus Fitting
- 1 Introduction
- 2 Annulus Fitting
- 2.1 Annulus Characterization
- 2.2 nD Annular Characterizations
- 3 Fitting Algorithm
- 3.1 Dual Space and Annulus Fitting in nD
- Cham : Springer, 2015.
- Description
- Book — 1 online resource (xx, 251 pages) : illustrations Digital: text file.PDF.
- Summary
-
- Semi-supervised Learning Algorithm for Binary Relevance Multilabel Classification
- On the Information Diffusion between Web-based Social Networks
- Generic Private Social Network for Knowledge Management
- Analysis of Event Logs: Behavioral Graphs
- Delineating Worker-Centered Organizational Work: Blending BPMS and Social Software Features
- Compliance of the LinkedIn Privacy Policy with the Principles of the ISO 29100:2011 Standard
- The Use of Social Tagging in Social Business Process Management SocIoS API: A Data Aggregator for Accessing User Generated Content from Online Social Networks
- Integrating Social Media and Open Data in a Cloud-based Platform for Public Sector Advertising
- A Survey on Approaches to Modeling Artifact-centric Business Processes
- A Connectivity-Based Recommendation Approach for Data Service Mashups
- Using Incentives to Analyze Social Web Services Behaviors Creating and Modelling Personal Socio-Economic Networks in On-Line Banking
- Cloud-based Video Monitoring Framework: An Approach based on Software-Defined Networking for Addressing Scalability Problems
- Context-awareness in Task Automation Services by Distributed Event Processing
- Data Streams Quality Evaluation for the Generation of Alarms in Health Domain
- Multilayer and Multi-agent Data Fusion in WSN
- Strategies for Data Quality Monitoring in Business Processes Quality Improvement Framework for Business Oriented Geo-Spatial Data.
- International Symposium on Mathematical Morphology and its Applications to Image and Signal Processing (13th : 2017 : Fontainebleau, France)
- Cham : Springer, 2017.
- Description
- Book — 1 online resource (XIV, 500 pages) : illustrations Digital: text file.PDF.
- Summary
-
- Algebraic Theory, Max-Plus and Max-Min Mathematics.- Discrete Geometry and Discrete Topology.- Watershed and Graph-based Segmentation.- Trees and Hierarchies.- Topological and Graph-based Clustering, Classification and Filtering.- Connected Operators and Attribute Filters.- PDE-based Morphology.- Scale-Space Representations and Nonlinear Decompositions.- Computational Morphology.- Object Detection.- Biomedical, Material Science and Physical Applications.
- (source: Nielsen Book Data)
(source: Nielsen Book Data)
- Singh, Himanshu, author.
- [Berkeley, California] : Apress, [2019]
- Description
- Book — 1 online resource Digital: text file; PDF.
- Summary
-
- Chapter 1: Installation and Environment Setup
- Chapter Goal: Making System Ready for Image Processing and Analysis
- No of pages 20
- Sub -Topics (Top 2)
- 1.
- Installing Jupyter Notebook
- 2.
- Installing OpenCV and other Image Analysis dependencies
- 3.
- Installing Neural Network Dependencies
- Chapter 2: Introduction to Python and Image Processing
- Chapter Goal: Introduction to different concepts of Python and Image processing Application on it.
- No of pages: 50
- Sub - Topics (Top 2)
- 1. Essentials of Python
- 2. Terminologies related to Image Analysis
- Chapter 3: Advanced Image Processing using OpenCV
- Chapter Goal: Understanding Algorithms and their applications using Python
- No of pages: 100
- Sub - Topics (Top 2):
- 1.
- Operations on Images
- 2.
- Image Transformations
- Chapter 4: Machine Learning Approaches in Image Processing
- Chapter Goal: Basic Implementation of Machine and Deep Learning Models, which takes care of Image Processing, before applications in real-time scenario
- No of pages: 100
- Sub - Topics (Top 2):
- 1.
- Image Classification and Segmentation
- 2.
- Applying Supervised and Unsupervised Learning approaches on Images using Python
- Chapter 5: Real Time Use Cases
- Chapter Goal: Working on 5 projects using Python, applying all the concepts learned in this book
- No of pages: 100
- Sub - Topics (Top 5):
- 1. Facial Detection
- 2. Facial Recognition
- 3. Hand Gesture Movement Recognition
- 4. Self-Driving Cars Conceptualization: Advanced Lane Finding
- 5. Self-Driving Cars Conceptualization: Traffic Signs Detection
- Chapter 6: Appendix A
- Chapter Goal: Advanced concepts Introduction
- No of pages: 50
- Sub - Topics (Top 2):
- 1. AdaBoost and XGBoost
- 2. Pulse Coupled Neural Networks.
- (source: Nielsen Book Data)
(source: Nielsen Book Data)
- Asian Conference on Computer Vision (13th : 2016 : Taipei, Taiwan)
- Cham, Switzerland : Springer, 2017.
- Description
- Book — 1 online resource (xiii, 434 pages) : illustrations Digital: text file.PDF.
- Summary
-
- Segmentation and Classification.- Segmentation and Semantic Segmentation.- Dictionary Learning, Retrieval, and Clustering.- Deep Learning.- People Tracking and Action Recognition.- People and Actions.- Faces.- Computational Photography.- Face and Gestures.- Image Alignment.- Computational Photography and Image Processing.- Language and Video.- 3D Computer Vision.- Image Attributes, Language, and Recognition.- Video Understanding.- 3D Vision.
- (source: Nielsen Book Data)
(source: Nielsen Book Data)
- Asian Conference on Computer Vision (13th : 2016 : Taipei, Taiwan). jointly held conference. jointly held conference.
- Cham, Switzerland : Springer, 2017.
- Description
- Book — 1 online resource (xxv, 652 pages) : illustrations Digital: text file.PDF.
- Summary
-
- New Trends in Image Restoration and Enhancement (NTIRE).- Workshop on Assistive Vision.- Hyperspectral Image and Signal Processing.- Computer Vision Technologies for Smart Vehicle.- Spontaneous Facial Behavior Analysis.- 3D Modelling and Applications.
- (source: Nielsen Book Data)
(source: Nielsen Book Data)
- Asian Conference on Computer Vision (13th : 2016 : Taipei, Taiwan). jointly held conference. jointly held conference.
- Cham, Switzerland : Springer, 2017.
- Description
- Book — 1 online resource (xv, 640 pages) : illustrations Digital: text file.PDF.
- Summary
-
- New Trends in Image Restoration and Enhancement (NTIRE).- Workshop on Assistive Vision.- Hyperspectral Image and Signal Processing.- Computer Vision Technologies for Smart Vehicle.- Spontaneous Facial Behavior Analysis.- 3D Modelling and Applications.
- (source: Nielsen Book Data)
(source: Nielsen Book Data)
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