Intro
Preface
Organization
Contents - Part II
Contents - Part I
Machine Learning and Computer Vision
Point Clouds Registration Algorithm Based on Spatial Structure Similarity of Visual Keypoints
1 Introduction
2 Method
2.1 2D Visual Keypoints
2.2 Depth Completion and Back-Project
2.3 Screening 3D Keypoints
2.4 Rigid Transformation Parameter Estimation
3 Experiment
3.1 Data and Metrics
3.2 Experiment and Comparison
4 Conclusion
References
Software Defect Prediction Based on SMOTE-Tomek and XGBoost
1 Introduction
2 Related Work
2.1 Sampling Technique
2.2 Cost-Sensitive Learning
2.3 Ensample Learning Algorithm
3 The Proposed Model
3.1 SMOTE-Tomek
3.2 XGBoost
3.3 STX Model
4 Experiments
4.1 Datasets
4.2 Performance Measures
4.3 Results and Discussion
4.4 Statistical Comparison of Software Defect Predictors
5 Conclusion
References
Imbalance Classification Based on Deep Learning and Fuzzy Support Vector Machine
1 Introduction
2 Related Work
2.1 Data-Level
2.2 Algorithm-Level
3 Proposed Method
3.1 Feature Extraction with Deep Learning
3.2 Random Feature Oversampling Based on Center Distance
3.3 Fuzzy Support Vector Machine
4 Experiments and Results
4.1 Evaluation Metrics and Datasets
4.2 Experiment Settings
4.3 Results and Analysis
5 Conclusion
References
Community Detection Based on Surrogate Network
1 Introduction
2 Preliminaries
2.1 Spectral Clustering
2.2 EA-Based Community Detection
3 Proposed Method
4 Experiments
4.1 Experimental Setup
4.2 Experimental Results and Discussions
5 Conclusions
References
Fault-Tolerant Scheme of Cloud Task Allocation Based on Deep Reinforcement Learning
1 Introduction
2 Related Works
3 Cloud System and Fault Model.

3.1 Task Model
3.2 Fault Model
3.3 APSDQN MDP Model
4 APSDQN Implementation
5 Simulation Experiment
5.1 Experimental Setup
5.2 Experimental Results and Analysis
6 Conclusion
References
Attention-Guided Memory Model for Video Object Segmentation
1 Introduction
2 Related work
3 Methodology
3.1 Network Overview
3.2 Joint Attention Guider
3.3 Spatial-Temporal Feature Fusion
3.4 Implementation of Other Modules
3.5 Network Training
4 Experiments
4.1 Comparision to State-of-the-Art
4.2 Ablation Study
5 Conclusion
References
Multi-workflow Scheduling Based on Implicit Information Transmission in Cloud Computing Environment
1 Introduction
2 Workflow Schedule Model
2.1 Workflow Model
2.2 Problem Expression
3 Multifactorial Evolutionary Algorithm for DAG Schedule
3.1 MFEA Based on Combinatorial Population (CP-MFEA)
3.2 Generation of Population
3.3 Generation of Offspring
3.4 Evaluate Offspring
4 Experiment and Discuss
4.1 Basic Workflow Structure
4.2 Experimental Setup
4.3 Results and Analysis
5 Conclusion
References
Pose Estimation Based on Snake Model and Inverse Perspective Transform for Elliptical Ring Monocular Vision
1 Introduction
2 Ellipse Ring Contour Extraction Based on Snake Model
2.1 Rough Contour Extraction
2.2 Refined Contour Extraction
3 Ellipse Correction Based on Inverse Perspective Transformation
3.1 Solving Inverse Perspective Transformation Matrix
3.2 Ellipse Correction and Pose Estimation
4 Experimental Results and Analysis
5 Conclusion
References
Enhancing Aspect-Based Sentiment Classification with Local Semantic Information
1 Introduction
2 Related Work
3 Preliminaries
4 Methodology
4.1 Embedding and Bidirectional LSTM
4.2 Obtaining Semantic Information.

4.3 FMDG: Obtaining Local Semantic Information
4.4 Information Fusion
4.5 Sentiment Classification
4.6 Training
5 Experiments
5.1 Dataset and Experiment Setup
5.2 Models for Comparison
5.3 Overall Result
5.4 Ablation Study
6 Conclusion
References
A Chinese Dataset Building Method Based on Data Hierarchy and Balance Analysis in Knowledge Graph Completion
1 Introduction
2 Problem Analysis
2.1 Existence of Meaningless Triples
2.2 Unbalanced Data Volume
3 Methods
3.1 Use Indicators to Measure Dataset Structure
3.2 Method of Constructing Chinese Dataset
3.3 Knowledge Graph Completion Model Selection
4 Experiments
5 Conclusions
References
A Method for Formation Control of Autonomous Underwater Vehicle Formation Navigation Based on Consistency
1 Introduction
2 AUV Formation System Description
2.1 Graph Theory
2.2 Kinematic Model
2.3 Information Interaction Model
3 Formation Control Algorithm Design
3.1 Definition of Covariate
3.2 Second-Order Consistency Control Algorithm
3.3 Model Predictive Control Rate Design
4 Simulation Research
4.1 Simulation Setup
4.2 Simulation Results and Analysis
5 Conclusion
References
A Formation Control Method of AUV Group Combining Consensus Theory and Leader-Follower Method Under Communication Delay
1 Introduction
2 Preliminaries and Modelling
2.1 Graph Theory
2.2 AUV Model
2.3 Communication Modelling
3 Consistency Control Algorithm Based on Leader-Following Method for AUV Group
3.1 Consistency Control Algorithm Without Communication Delay
3.2 Consistency Control Algorithm with Communication Delay
4 Simulation Results
4.1 Simulation of Consistency Control Algorithm Without Communication Delay
4.2 Simulation of Consistency Control Algorithm with Communication Delay
5 Conclusion.

4.2 Simulation of Heterogeneous AUV Cluster Consistency Algorithm with Time Delay Under Event Trigger Control
5 Conclusion
References
Edge Computing Energy-Efficient Resource Scheduling Based on Deep Reinforcement Learning and Imitation Learning
1 Introduction
2 Related Works
3 Scheduling System
3.1 Workload Processor
3.2 Problem Definition
3.3 Environment Model
4 Simulation Experiment
5 Conclusion
References
Metric Learning with Distillation for Overcoming Catastrophic Forgetting
1 Introduction
2 Related Work
2.1 Incremental Learning
2.2 Metric Learning
2.3 Knowledge Distillation
3 Proposed Method
3.1 Network Structure and its Losses
3.2 Knowledge Distillation Embedded in the Network
3.3 Classifier
4 Experiment
4.1 Datasets
4.2 Implementation Details
4.3 Ablation Experiment
4.4 Comparison Methods
5 Conclusions
References
Feature Enhanced and Context Inference Network for Pancreas Segmentation
1 Introduction
2 Related Work
2.1 Deep Learning Methods
2.2 Attention Mechanism
3 Methods
3.1 Feature Encoder
3.2 Feature Space Mapping
3.3 Feature Enhancement
3.4 Decoder
4 Experiment
4.1 Experiment Setup
4.2 Comparative Experiments
4.3 Comparative Experiments
5 Discussion and Conclusion
References
Object Relations Focused Siamese Network for Remote Sensing Image Change Detection
1 Introduction
2 Related Work
3 Methods
3.1 Basic Network Architecture
3.2 Geo-Objects Relations Module
3.3 Feature Enhancement
4 Experiment
4.1 Experiment Settings
4.2 Ablation Experiments
4.3 Comparative Experiments
5 Conclusion
References
MLFF: Multiple Low-Level Features Fusion Model for Retinal Vessel Segmentation
1 Introduction
2 Related Works
3 Multiple Low-Level Feature Fusion Model.