Pattern Recognition. ICPR International Workshops and Challenges

Name: Pattern Recognition. ICPR International Workshops and Challenges | Virtual Event, January 10-15, 2021, Proceedings, Part II
Brand: Springer
Price: 96.29 EUR
Availability: OnlineOnly

Virtual Event, January 10-15, 2021, Proceedings, Part II

Alberto Del Bimbo Rita Cucchiara Stan Sclaroff Giovanni Maria Farinella Tao Mei Marco Bertini Hugo Jair Escalante Roberto Vezzani(Editor)

Springer (Publisher)

Published on 22. February 2021

XX, 753 pages

E-Book

PDF with digital watermarking

System requirements

978-3-030-68790-8 (ISBN)

€96.29incl. 7% vat

System requirements

for PDF with digital watermarking

E-Book Single Licence

Available for download

Description

More details

Other editions

Content

Intro
Foreword by General Chairs
Preface
Challenges
ICPR Organization
Contents - Part II
CAIHA - Computational and Affective Intelligence in Healthcare Applications for Vulnerable Populations
CAIHA: Computational and Affective Intelligence in Healthcare Applications (Vulnerable Populations)
Organization
General Chair
Program Committee Chairs
Program Committee
Towards Robust Deep Neural Networks for Affect and Depression Recognition from Speech
1 Introduction
2 Related Work
2.1 Handcrafted Features-Based Approaches
2.2 Deep Learning-Based Approaches
3 Motivations and Contributions
4 Proposed Method
4.1 Data Augmentation
4.2 Spectrogram-Based CNN Stream
4.3 MFCC-Based CNN Stream
4.4 Aggregation of the Spectrogram-Based and MFCC-Based Responses
5 Experiments and Results
5.1 Datasets
5.2 Experimental Setup
5.3 Experimental Results on Spontaneous and Continuous Emotion Recognition from Speech
5.4 Experimental Results on Automatic Clinical Depression Recognition and Assessment
6 Conclusion and Future Work
References
COVID-19 and Mental Health/Substance Use Disorders on Reddit: A Longitudinal Study
1 Introduction
2 Related Work
3 Methods
3.1 Data Collection
3.2 Analysis
4 Results and Discussion
5 Conclusion and Future Work
References
Multi-stream Integrated Neural Networks for Facial Expression-Based Pain Recognition
1 Introduction
2 Proposed Method
2.1 3DConvNet
2.2 Optical Flow 3DConvNet
2.3 Stream Integration for Facial Expression of Pain
3 Experiments and Discussion
4 Conclusion
References
A New Facial Expression Processing System for an Affectively Aware Robot
1 Introduction
2 Related Work
3 LabelFace: A Facial Expression Processing Tool
4 Test Setup, Implementation and Experiments
4.1 Datasets
4.2 Proposed Method
5 Test Results and Discussions
6 Conclusion and Future Directions
References
Classification of Autism Spectrum Disorder Across Age Using Questionnaire and Demographic Information
1 Introduction
2 Experimental Design
2.1 Dataset
2.2 Experiments
3 Results
3.1 Within-Dataset Evaluation on Child, Adolescent, and Adult
3.2 Cross-Dataset Evaluation on Child, Adolescent, and Adult
3.3 Comparison to State of the Art
4 Conclusion
References
Neonatal Pain Scales and Human Visual Perception: An Exploratory Analysis Based on Facial Expression Recognition and Eye-Tracking
1 Introduction
2 Neonatal Pain
3 Materials and Methods
3.1 Volunteers
3.2 Hardware
3.3 Framework
3.4 Facial Regions of Interest
4 Results and Discussion
4.1 Proposed Regions of Interest by the Literature
4.2 Visualised Regions of Interest by Each Sample Group
5 Conclusions
References
Pain Intensity Assessment in Sickle Cell Disease Patients Using Vital Signs During Hospital Visits
1 Introduction
2 Related Work
3 Methods
3.1 Data Description
3.2 Pain Prediction
4 Results and Discussion
4.1 Intra-individual Pain Prediction
4.2 Inter-individual Pain Prediction
4.3 Pain Change Prediction
5 Conclusion
References
Longitudinal Classification of Mental Effort Using Electrodermal Activity, Heart Rate, and Skin Temperature Data from a Wearable Sensor
1 Introduction
2 Methods
2.1 Study Design
2.2 Description of the Case and Instrumentation
2.3 Markov Switching Regression Model
3 Results
3.1 Descriptive Analysis
3.2 Longitudinal Modeling of Mental Effort Using Physiological Data
4 Discussion and Conclusions
References
CARE2020 - International Workshop on pattern recognition for positive teChnology And eldeRly wEllbeing
First International Workshop on pattern recognition for positive teChnology And eldeRly wEllbeing (CARE 2020)
Organization
Program Committee Chairs
Program Committee
Additional Reviewer
Multimodal Physiological-Based Emotion Recognition
1 Introduction
2 Datasets
3 Proposed Method
4 Experimental Design
4.1 Deep Neural Network Architecture
4.2 BP4D+ Experimental Design
4.3 DEAP Experimental Design
5 Results
5.1 BP4D+
5.2 DEAP
5.3 State of the Art Comparisons
6 Conclusion
References
Combining Deep and Unsupervised Features for Multilingual Speech Emotion Recognition
1 Introduction
2 Related Works
3 Corpora
4 Features
4.1 Linguistic Features
4.2 Acoustic Features
5 Model
6 Experiments
7 Results
8 Conclusions
References
Towards Generating Topic-Driven and Affective Responses to Assist Mental Wellness
1 Introduction
2 Related Work
2.1 Conversational AI
2.2 Affect in Conversational AI
2.3 Controlled Text Generation
3 TACA - Topic-Driven Affective Conversational Agent
3.1 Affective Conversational Agent
3.2 Controlling a Topic in Conversation
4 TMoEL - Topic-Driven MoEL
4.1 Mixture of Empathetic Listeners
4.2 Steering Responses in MoEL Using PPLM
5 Experiments and Results
5.1 Qualitative Analysis
5.2 Quantitative Analysis
6 Conclusion
References
Keypoint-Based Gaze Tracking
1 Introduction
2 Related Work
3 Proposed Approach
3.1 Temporal Integration
4 Experiments and Results
4.1 Gaze Regression Performance
4.2 Temporal Integration Performance
5 Conclusion
References
Multimodal Empathic Feedback Through a Virtual Character
1 Introduction
2 Methods
3 Discussion and Future Works
4 Conclusion
References
A WebGL Virtual Reality Exergame for Assessing the Cognitive Capabilities of Elderly People: A Study About Digital Autonomy for Web-Based Applications
1 Introduction
2 Materials and Methods
2.1 The Virtual Supermarket Environment
2.2 The Software Framework
2.3 Collected Data
2.4 Experimental Procedure
2.5 Data Analysis
3 Results
4 Discussion and Conclusions
References
Daily Living Activity Recognition Using Wearable Devices: A Features-Rich Dataset and a Novel Approach
1 Introduction
2 Dataset of Daily Living Activities Creation
2.1 Data Recording
2.2 Raw Data Extraction
2.3 Data Labelling and Cleaning
3 A Possible Approach to Daily Living Activity Recognition
3.1 Features Extraction
3.2 Hyperparameter Tuning
3.3 Training Model to Predict Data
4 Empirical Evaluation of the Approach
4.1 Procedure
4.2 Results
5 Related Works
6 Conclusions and Future Work
References
Deep Neural Networks for Real-Time Remote Fall Detection
1 Introduction
2 Related Work in Computer Vision
3 Dataset
3.1 UR Fall Detection Dataset
3.2 Multiple Cameras Fall Dataset
3.3 Combined Dataset
4 Proposed Method
4.1 Pose Detection Model
4.2 Supplementary CNN
4.3 Extracting Poses
4.4 Classifying Series of Poses
5 Experiment
5.1 Experimental Results
5.2 Time Cost Analysis
5.3 Comparing with State of the Art
6 Conclusions
6.1 Future Developments
References
Mutual Use of Semantics and Geometry for CNN-Based Object Localization in ToF Images
1 Introduction
2 State of the Art
2.1 2D Convolutional Segmentation
2.2 3D Convolutional Localization
2.3 Segmentation and Localization Using Graph NNs
3 Floor Plan Estimation for Autonomous Object Localization
3.1 ToF Data
3.2 Method Overview
3.3 Floor and Object Segmentation (steps 1 and 3)
3.4 Localization and Error Estimation (steps 4 and 5)
4 Results and Analysis
4.1 Validation Methodology
4.2 Floor Segmentation and Floor Normal Estimation
4.3 Bed Segmentation and Localization Accuracy
4.4 Input Ablation
5 Conclusion
References
Development and Evaluation of a Mouse Emulator Using Multi-modal Real-Time Head Tracking Systems with Facial Gesture Recognition as a Switching Mechanism
1 Introduction
2 Background
2.1 Device Evaluation
2.2 Gesture Detection
3 Materials and Methods
3.1 Device Evaluation
3.2 Gesture Detection
4 Experimentation
4.1 Setup
4.2 Sensors
4.3 Depth Data
5 Result
6 Discussion
7 Conclusion
References
A Video-Based MarkerLess Body Machine Interface: A Pilot Study
1 Introduction
2 Methods
2.1 Automatic Body Landmarks Detection
2.2 Encoding Body Landmarks in the 2D Cursor Space
2.3 Online Video-Based Marker-Less BoMI
3 Pilot Test and Preliminary Results
3.1 Body Parts Detection's Accuracy
3.2 Online Test of the BoMI
4 Discussion, Conclusion and Future Work
References
Visual-Textual Image Understanding and Retrieval (VTIUR) - Joint Workshop on Content-Based Image Retrieval (CBIR 2020), Video and Image Question Answering (VIQA 2020), Texture Analysis, Classification and Retrieval (TAILOR 2020)
Visual-Textual Image Understanding and Retrieval (VTIUR) - Joint Workshop on Content-Based Image Retrieval (CBIR 2020), Video and Image Question Answering (VIQA 2020), Texture Analysis, Classification and Retrieval (TAILOR 2020)
Workshop Description
Organization
Program Committee (VIQA) Chairs
Program Committee (TAILOR) Chairs
Program Committee (CBIR) Chairs
Technical Program Committee (VIQA)
Technical Program Committee (TAILOR)
Technical Program Committee (CBIR)
Content-Based Image Retrieval and the Semantic Gap in the Deep Learning Era
1 Introduction
2 The Evolution of Instance Retrieval
2.1 Hand-Crafted Features and Visual Words
2.2 Off-the-Shelf CNN Features
2.3 End-to-End Learning for Image Retrieval
3 Impact on the Semantic Gap
4 Knowledge Integration for Semantic Image Retrieval
4.1 Class Labels
4.2 Class Taxonomies
4.3 Textual Descriptions
4.4 Artistic Style
5 The Missing Ingredient
6 Conclusions
References
A Modality Converting Approach for Image Annotation to Overcome the Inconsistent Labels in Training Data
1 Introduction
2 Related Work
3 Proposed Method
3.1 Feature Extraction from a Convolutional Neural Network
3.2 Modality Conversion
3.3 Classification
4 Experiments
4.1 Experimental Setting
4.2 Result
5 Discussion and Conclusion
References
Iconic-Based Retrieval of Grocery Images via Siamese Neural Network
1 Introduction and Related Work
2 Materials
3 Method
3.1 Learned Features
4 Experiments
4.1 Retrieval Measures
4.2 Results
5 Conclusion
References
Garment Recommendation with Memory Augmented Neural Networks
1 Introduction
2 Related Work
2.1 Recommendation Systems
2.2 Garment Recommendation
2.3 Memory Augmented Networks
3 Garment Recommendation with MANNs
3.1 Feature Representation
3.2 Model
3.3 General Recommendations and User Preferences
4 Experiments
4.1 Dataset and Metrics
4.2 Results
5 Conclusions
References
Developing a Smart PACS: CBIR System Using Deep Learning
1 Introduction
2 Developing a Smart PACS
2.1 Proposed Architecture
2.2 Convolutional Neural Networks as Features Extractors
3 Results
4 Conclusions
References
Multi Color Channel vs. Multi Spectral Band Representations for Texture Classification
1 Introduction
2 Color and Spectral Texture Features
2.1 Cooccurrence Matrices
2.2 Local Binary Pattern
3 Dimensionality Reduction
3.1 Feature Selection
3.2 Histogram Selection
4 Experiments
4.1 Image Databases
4.2 Texture Classification
4.3 Results and Discussions
5 Conclusion
References
Multi-task Learning for Supervised and Unsupervised Classification of Grocery Images
1 Introduction
2 Related Work
3 Materials
4 Methods
4.1 Baseline
4.2 Multi-task Network
4.3 Supervised Classification Using Learned Features
4.4 Unsupervised Classification
5 Experiments
5.1 Baseline Results
5.2 Results of Supervised Classification
5.3 Results of Unsupervised Classification
6 Conclusion
References
Recent Advances in Video Question Answering: A Review of Datasets and Methods
1 Introduction
2 Datasets
2.1 MovieQA
2.2 YouTube2TextQA
2.3 MSRVTT-QA and MSVD-QA
2.4 VideoQA
2.5 Pororo-QA
2.6 TVQA+ and TVQA
2.7 ActivityNet-QA
2.8 TGIF-QA
2.9 LifeQA
2.10 DramaQA
2.11 Social-IQ
2.12 MarioQA
2.13 EgoVQA
2.14 Tutorial-VQA
2.15 KnowIT-VQA
3 Methods
3.1 Spatio-Temporal Methods
3.2 Memory-Based Methods
3.3 Attention-Based Methods
3.4 Multimodal Attention Based Methods
3.5 Miscellaneous Models
4 Discussion
References
IQ-VQA: Intelligent Visual Question Answering
1 Introduction
2 Related Works
3 Approach
3.1 Implication Generator Module
3.2 Knob Mechanism
3.3 Cyclic Framework
4 Experiments Setup
4.1 Datasets
4.2 VQA Models
4.3 Implementation Details
5 Results and Analysis
5.1 Consistency Performance
5.2 Robustness Performance
5.3 Attention Map Analysis
5.4 Data Augmentation
5.5 Implication Generator Performance
6 Conclusion and Future Works
References
CVAUI 2020 - 4th Workshop on Computer Vision for Analysis of Underwater Imagery
Preface
Organization
Workshop Chairs
Program Committee
Deep Sea Robotic Imaging Simulator
1 Introduction
2 Related Work and Main Contributions
3 Deep Sea Image Formation Model
3.1 Radiation of the Light Source
3.2 Attenuation and Reflection
3.3 Scattering
4 Implementation
4.1 Optimizations for Rendering
4.2 Rendering Results
4.3 Integration in Robotic UUV Simulation Platform
5 Evaluation
6 Conclusion
References
Optimization of Multi-LED Setups for Underwater Robotic Vision Systems
1 Introduction and Previous Work
2 Multiple Light Configuration Optimization
2.1 Underwater Image Simulation
2.2 Evaluation Factors
2.3 Optimization Algorithms
3 Implementation and Test Results
4 Conclusion and Further Work
References
Learning Visual Free Space Detection for Deep-Diving Robots
1 Introduction
2 Previous Work and Contributions
3 Segmentation Approaches
3.1 Gaussian Mixture Models (GMM) in Color Space
3.2 Markov Random Field (MRF) Based Segmentation
3.3 Deep Learning Based Approach
3.4 Efficiently Obtaining Masks for Training
4 Implementation Details
4.1 Model Hyperparameters
4.2 Other Details
5 Evaluation
5.1 Influence of CNN Parameters
5.2 Training Time and Prediction Time
5.3 Analysis of All the Methods
5.4 SLAM/SfM Reconstruction
6 Conclusion
References
Removal of Floating Particles from Underwater Images Using Image Transformation Networks
1 Introduction
2 Method Description
3 Experimental Study
3.1 Dataset
3.2 Training Details
3.3 Results
4 Conclusions
References
Video-Based Hierarchical Species Classification for Longline Fishing Monitoring
1 Introduction
1.1 Electronic Monitoring (EM) of Fisheries
1.2 Hierarchical Classification
2 Related Work
2.1 Flat Classifiers
2.2 Hierarchical Classifier
3 Proposed Method
3.1 Hierarchical Dataset
3.2 Hierarchical Architecture
4 Experiments and Discussion
4.1 Data Split
4.2 Baseline
4.3 Evaluation Methods
4.4 Ablation Study
5 Conclusions and Future Work
References
Robust Fish Enumeration by Multiple Object Tracking in Overhead Videos
1 Introduction
2 Related Work
3 Methodology
3.1 Video Collection
3.2 Fish Tracking
3.3 Trajectory Refinement and Counting Zone Generation
3.4 Fish Counting
4 Experiments
5 Conclusion
References
DEEPRETAIL 2020 - Workshop on Deep Understanding Shopper Behaviours and Interactions in Intelligent Retail Environments 2020
Workshop on Deep Understanding Shopper Behaviours and Interactions in Intelligent Retail Environments (Deep Retail)
Workshop Description
Organization
Scientific Committee
Industrial Committee
3D Vision-Based Shelf Monitoring System for Intelligent Retail
1 Introduction
2 Related Work
3 3D Vision-Based Shelf Monitoring (3D-VSM)
3.1 Shelf Modeling and ROI Selection
3.2 Product OSA Estimation
3.3 Integration in the E-SHELF Platform
4 Experimental Results
5 Conclusion
References
Faithful Fit, Markerless, 3D Eyeglasses Virtual Try-On
1 Introduction
2 Related Work
3 Proposed Method
3.1 3D Face Reconstruction
3.2 Face Size Estimation
3.3 Glasses Try-On
4 Conclusions and Future Works
References
Performance Assessment of Face Analysis Algorithms with Occluded Faces
1 Introduction
2 The Architectures
2.1 Gender Recognition
2.2 Ethnicity Recognition
2.3 Age Estimation
2.4 Emotion Recognition
3 Dataset
4 Experimental Analysis
4.1 Gender Recognition Results
4.2 Ethnicity Recognition Results
4.3 Age Estimation Results
4.4 Emotion Recognition Results
5 Discussion
6 Conclusions
References
Who Is in the Crowd? Deep Face Analysis for Crowd Understanding
1 Introduction
2 Crowd Understanding System
2.1 Face Detection
2.2 Demographic and Sentiment Analysis of Facial Images
2.3 Summarize and Display Statistics
3 Discussion
4 Conclusions
References
A Saliency-Based Technique for Advertisement Layout Optimisation to Predict Customers' Behaviour
1 Introduction
2 Related Techniques
3 Proposed Method
4 Experimental Results
5 Conclusions and Future Works
References
Data-Driven Knowledge Discovery in Retail: Evidences from the Vending Machine's Industry
1 Introduction
2 Big Data Analytics
3 Theoretical Background and Research Methodology
4 The System Technology
5 Experimental Results
6 Conclusions
References
People Counting on Low Cost Embedded Hardware During the SARS-CoV-2 Pandemic
1 Introduction
2 Related Works
3 Materials and Methods
3.1 Dataset
3.2 Deep Learning Model
3.3 Mosse Tracking
3.4 Performance Evaluation
3.5 Hardware Setup
4 Results and Discussion
5 Conclusions and Future Works
References
Shoppers Detection Analysis in an Intelligent Retail Environment
1 Introduction
2 Related Works
3 Materials and Methods
3.1 Setup and Configuration
3.2 Shoppers Dataset
3.3 Classification Model
4 Results and Discussions
5 Conclusions and Future Works
References
DLPR - Deep Learning for Pattern Recognition
Preface
Organization
General Chairs
Program Committee
Recurrent Graph Convolutional Network for Skeleton-Based Abnormal Driving Behavior Recognition
1 Introduction
2 Related Work
3 Approach
3.1 Overall Architecture
3.2 Our Spatial Topological Graph
3.3 Our Graph Conventional Network Part
3.4 LSTM Network Part
4 Experiments
4.1 Our Driving Dataset
4.2 Kinetics Dataset
4.3 Implementation
4.4 Comparative Experiments
4.5 Ablation Study and Confusion Matrix
5 Conclusion
References
Supervised Autoencoder Variants for End to End Anomaly Detection
1 Introduction
2 Related Work
3 Background
3.1 Autoencoders for Outlier and Novelty Detection
3.2 Supervised Autoencoders
4 Adversarial Supervised Autoencoders
5 Experiments and Results
5.1 Datasets
5.2 Results
6 Conclusion
References
Fuzzy-Based Pseudo Segmentation Approach for Handwritten Word Recognition Using a Sequence to Sequence Model with Attention
1 Introduction
2 Related Work
2.1 Segmentation Free Word Recognition Models
2.2 Fuzzy-Based Word Segmentation
2.3 Motivation
3 Proposed Method
3.1 Skew and Slant Correction
3.2 Fuzzy-Based Pseudo Segmentation
3.3 Basic Recognition Architecture
3.4 CNN Architecture
3.5 Sequence to Sequence Model
4 Results
4.1 Dataset and Evaluation Metrics Used
4.2 Optimizing the Parameters of the Word Recognition Model
4.3 Comparisons
4.4 Error Case Analysis
5 Conclusion and Future Work
References
Bifurcated Autoencoder for Segmentation of COVID-19 Infected Regions in CT Images
1 Introduction
2 Proposed Method
2.1 Architecture
2.2 Loss Functions
3 Experimental Results
4 Conclusion
References
DeepPBM: Deep Probabilistic Background Model Estimation from Video Sequences
1 Introduction
1.1 Overview of Background Subtraction Techniques
2 Proposed DeepPBM Estimation Approach
2.1 Probabilistic Modeling of the Background in Videos
2.2 DeepPBM Architecture and Training
3 Performance Assessment
4 Conclusion
References
Tracker Evaluation for Small Object Tracking
1 Introduction
2 Related Works
3 Experiments
3.1 Evaluation Dataset
3.2 Implementation Details
3.3 Experiments Results
3.4 Experiments Analysis
4 Conclusion
References
DepthOBJ: A Synthetic Dataset for 3D Mesh Model Retrieval
1 Introduction
1.1 Main Contributions
1.2 Organization of the Paper
2 Related Works
2.1 Single-View and Multi-view Approaches
2.2 Depth Maps
2.3 Deep Neural Networks
2.4 Output Types
3 Datasets
3.1 ShapeNetCore V2
3.2 Methodology
3.3 Criteria of Choice
3.4 Evaluation of the Dataset
4 Proposed Method
4.1 Real-Time Augmentation
4.2 Model
4.3 Training
4.4 Visualizer
5 Experiments
5.1 Architectures
5.2 Results
6 Conclusions
References
GFTE: Graph-Based Financial Table Extraction
1 Introduction
2 Related Work
2.1 Previous Datasets
2.2 Methods
3 Dataset Collection
4 Baseline Algorithm
5 Evaluation Results
6 Conclusion
References
Relative Attribute Classification with Deep-RankSVM
1 Introduction
2 Related Works
2.1 Traditional Approaches
2.2 Deep Learning Approaches
3 Deep-RankSVM
4 Experimental Evaluation
4.1 Datasets
4.2 Implementation Details
4.3 Results
4.4 Discussion
5 Summary and Future Work
References
Adversarial Continuous Learning in Unsupervised Domain Adaptation
1 Introduction
2 Related Work
3 Methods
3.1 Motivation
3.2 Problem and Notation
3.3 Source Classifier
3.4 Adversarial Domain Loss
3.5 Deep Correlation Loss
3.6 Continuous Learning
3.7 Shared Encoder Layers
3.8 A Two-Level Dynamic Distribution Alignment
3.9 The Overall Training Objective Function
4 Experiments
4.1 Datasets
4.2 Implementation Details
4.3 Results
4.4 Ablation Study
5 Discussion
6 Conclusion
References
A Survey of Deep Learning Based Fully Automatic Bone Age Assessment Algorithms
1 Introduction
2 Basic Medical Methods of BAA
3 Traditional Bone Extraction Method
4 Deep Learning Based BAA
4.1 Framework of Deep Learning Algorithm for BAA
4.2 Deep Neural Network Model Used in BAA
4.3 Results
5 Discussions
6 Conclusion
References
Unsupervised Real-World Super-resolution Using Variational Auto-encoder and Generative Adversarial Network
1 Introduction
2 Related Works
3 Proposed Method
3.1 Loss Functions
4 Experimental Results
4.1 Training Details and Hyper-parameter Tuning
4.2 Ablation Study
4.3 Quantitative Analysis
4.4 Qualitative Analysis
5 Conclusion
References
Training of Multiple and Mixed Tasks with a Single Network Using Feature Modulation
1 Introduction
2 Related Work
3 Proposed Method
3.1 Task Conditional Vector
3.2 FiLM-Based Network Architecture
3.3 Training of Mixed Tasks
4 Experiments
4.1 Task Sets for the Experiments
4.2 Experiment 1: Learning of Multiple Different Tasks
4.3 Experiment 2: Learning of Mixed Tasks
4.4 Experiment 3: Comparison to the Baselines
5 Conclusions
References
Deep Image Clustering Using Self-learning Optimization in a Variational Auto-Encoder
1 Introduction
2 Related Works
3 Proposed Approach
3.1 MVAE
3.2 Enhanced Clustering Optimization (EC)
3.3 Training
4 Experiments and Discussion
4.1 Datasets and Evaluation Metrics
4.2 Image Reconstruction
4.3 Analysis of Training Strategies
4.4 Comparison with State of the Art Methods
5 Conclusion
References
Author Index

System requirements

Save as PDF Copy link into clipboard

Schweitzer Fachinformationen

Pattern Recognition. ICPR International Workshops and Challenges

Description

More details

Other editions

Additional editions

Content

System requirements