Nonlinear Dynamics of Time Delay Systems: Methods and Applications

✍ Scribed by Jian Xu

• Publisher: Springer
• Year: 2024
• Tongue: English
• Leaves: 599
• Edition: 1st ed. 2024
• Category: Library

✦ Synopsis

This book presents research advancements in the dynamics of systems with time delay conducted by the group led by Professor Jian Xu. Addressing the challenges arising from the joint impact of time delay and nonlinearity, novel theoretical approaches are developed to formulate the nonlinear response of the system. This facilitates the classification of complex nonlinear dynamics, especially the non-resonant and resonant double Hopf bifurcation. In contrast to systems without time delay, time delay systems require specific considerations when identifying system parameters, particularly the time delay. Consequently, inverse problems of systems with time delay are also explored in this book. Moreover, detailed investigations on vibration suppression methods and experimental prototypes based on time delay, such as time delay isolators with quasi-zero stiffness, are conducted. Simultaneously, this book is enriched with a large number of case studies ranging from manufacturing, network science, biology, and public transportation, illuminating the mechanisms of delay-induced nonlinear dynamics in practical applications. This book is suitable for graduate students and researchers who are eager to understand the delay-induced nonlinear dynamics, or technical personnel in whose projects small variations of time delay may cause significant changes in system responses.

✦ Table of Contents

Preface
Organization
Contents – Part I
Contents – Part II
Computer Vision
MARS: An Instance-Aware, Modular and Realistic Simulator for Autonomous Driving
1 Introduction
2 Method
2.1 Scene Representation
2.2 Compositional Rendering
2.3 Towards Realistic Rendering
2.4 Optimization
3 Experiments
3.1 Photorealistic Rendering
3.2 Instance-Wise Editing
3.3 The Blessing of Modular Design
3.4 Ablation Results
4 Conclusion
References
Concealed Object Segmentation with Hierarchical Coherence Modeling
1 Introduction
2 Related Works
3 Methodology
3.1 Concealed Feature Encoder
3.2 Hierarchical Coherence Modeling
3.3 Reversible Re-calibration Decoder
3.4 Loss Functions
4 Experiments
4.1 Camouflaged Object Segmentation
4.2 Polyp Image Segmentation
4.3 Transparent Object Detection
4.4 Ablation Study and Further Analysis
5 Conclusions
References
ViT-MPI: Vision Transformer Multiplane Images for Surgical Single-View View Synthesis
1 Introduction
2 Related Work
3 Approach
3.1 MPI Representation and Rendering Using Single-View
3.2 Vision Transformer Backbone
4 Experiments
4.1 Dataset and Training Objective
4.2 Comparison
4.3 Ablation Studies
5 Conclusion
References
Dual-Domain Network for Restoring Images from Under-Display Cameras
1 Introduction
2 Related Work
2.1 UDC Image Enhancement
2.2 Retinex-Based Visual Models
2.3 Frequency Domain Enhancement Methods
3 Methodology
3.1 Retinex-Based Image Decomposition
3.2 Amplitude-Phase Mutual Guided Block
3.3 Multi-scale Hybrid Dilation Convolution Block
3.4 Training Loss
4 Experiments
4.1 Datasets and Training Procedure
4.2 Results
4.3 Ablation Study
5 Conclusion
References
Sliding Window Detection and Distance-Based Matching for Tracking on Gigapixel Images
1 Introduction
2 Related Work
2.1 Region Proposal Convolutional Detectors
2.2 Multi-object Tracking
3 Methodology
3.1 Preliminary
3.2 Multi-sclae Sliding Window
3.3 Distance-Based Tracking Strategy
4 Experiment
4.1 Datasets and Metrics
4.2 Implementation Details
4.3 Comparsion with Other Method
4.4 Ablation Study
5 Conclusion
References
Robust Self-contact Detection Based on Keypoint Condition and ControlNet-Based Augmentation
1 Introduction
2 Related Work
2.1 Contact Detection
2.2 3D Body Dataset
2.3 Generation for Generalization
3 Method
3.1 Definition
3.2 Self-contact Data Generation
3.3 Method: RSCD
4 Experiments
4.1 Implementation Details
4.2 Results
4.3 Evaluation on Keypoint Condition
5 Ablation Studies
5.1 Generation to Generalization
6 Limitations
7 Conclusions
References
Explicit Composition of Neural Radiance Fields by Learning an Occlusion Field
1 Introduction
2 Related Work
3 Method
3.1 Preliminaries
3.2 Occlusion Field
3.3 Composition Rendering Equation
3.4 Model Training
4 Experiment
4.1 Data Preparation
4.2 Qualitative Evaluation
4.3 Comparison
4.4 Ablation Studies
5 Conclusion
References
LEAD: LiDAR Extender for Autonomous Driving
1 Introduction
2 Related Work
2.1 Depth Estimation
2.2 Depth Completion
3 Method
3.1 Overview
3.2 Self-supervised Teacher Network (STN)
3.3 Propagative Probabilistic Generator (PPG)
3.4 Probabilistic Derivation and Composition
3.5 Network Training
4 Experiment
4.1 Hardware and Evaluation Dataset
4.2 Qualitative Results
4.3 Quantitative Results
5 Conclusion
References
Fast Hierarchical Depth Super-Resolution via Guided Attention
1 Introduction
2 Related Work
2.1 Traditional Depth SR Method
2.2 Deep Learning-Based Depth SR Method
3 Proposed Method
3.1 Framework Overview
3.2 Structures of Main and Side Branches
3.3 Guided Attention
4 Experiments and Results
4.1 Implementation Details
4.2 Comparison with SOTA Methods
4.3 Attention Analysis
4.4 Running Time
5 Conclusion
References
A Hybrid Approach for Segmenting Non-ideal Iris Images Using CGAN and Geometry Constraints
1 Introduction
2 Related Work
3 Methods
3.1 Iris Segmentation Using CGAN
3.2 Objective
3.3 Network Architecture
3.4 Refinement Using Geometry Constraints
4 Experiments
4.1 Datasets
4.2 Evaluation Metrics
4.3 Implementation Details
4.4 Comparision with the State of the Art
5 Conclusion
References
3D-B2U: Self-supervised Fluorescent Image Sequences Denoising
1 Introduction
2 Related Work
2.1 Image Denoising
2.2 Self-supervised Denoising on Fluorescence Images
3 Method
3.1 Motivation
3.2 Framework
3.3 3D Global Masker
4 Experimental Results
4.1 Experimental Settings
4.2 Synthetic Data Denoising
4.3 Real Data Denoising
5 Ablation
6 Conclusion
References
Equivariant Indoor Illumination Map Estimation from a Single Image
1 Introduction
2 Related Work
3 Method
3.1 Overall Architecture
3.2 Point Cloud Generation
3.3 Equivariant Illumination Estimation
3.4 Loss
4 Experiment
4.1 Datasets and Preprocessing
4.2 Comparison in Quality and Quantity
4.3 Ablation Study
4.4 Application on AR
5 Conclusion
References
Weakly-Supervised Grounding for VQA with Dual Visual-Linguistic Interaction
1 Introduction
2 Related Work
2.1 Visual Question Answering
2.2 VQA Grounding
3 Method
3.1 Architecture
3.2 Language-Based Visual Decoder
3.3 Pseudo Grounding Refinement
3.4 Training Objectives
4 Experiments
4.1 Training Details
4.2 Ablation Study
5 Comparison with State-of-the-Arts
6 Conclusion
References
STU3: Multi-organ CT Medical Image Segmentation Model Based on Transformer and UNet
1 Introduction
2 Method
2.1 Architecture Overview
2.2 SWTB
2.3 Local Part
2.4 Global Part and RFFF
2.5 Glfb
3 Experiments
3.1 Implementation Details
3.2 Evaluating Metric
3.3 Experimental Result
4 Conclusion
References
Integrating Human Parsing and Pose Network for Human Action Recognition
1 Introduction
2 Related Work
2.1 Human Action Recognition
2.2 Human Parsing
3 IPP-Net
3.1 Human Pose Learning
3.2 Human Parsing Learning
3.3 Integration
4 Experiments
4.1 Datasets
4.2 Implementation Details
4.3 Comparison with Related Methods
4.4 Ablation Study
5 Conclusions
References
Lightweight Rolling Shutter Image Restoration Network Based on Undistorted Flow
1 Introduction
2 Related Works
3 Approach
3.1 Problem Formulation
3.2 Architecture Overview
3.3 Extract Feature Pyramid
3.4 Generate Bidirectional Optical Flow
3.5 Time Factor and Undistortion Flow
3.6 Losses
4 Experiment
4.1 Datasets
4.2 Evaluation Strategies
4.3 Comparison with SOTA Methods
4.4 Ablation Studies
5 Conclusion
References
An Efficient Graph Transformer Network for Video-Based Human Mesh Reconstruction
1 Introduction
2 Related Work
2.1 Human Mesh Reconstruction
2.2 Graph Convolutional Networks
3 Method
3.1 Overview of EGTR
3.2 Temporal Redundancy Removal
3.3 Spatial-Temporal Fusion
3.4 Multi-branch Integration
3.5 Loss Function
4 Experiments
4.1 Experimental Settings
4.2 Comparison with State-of-the-Art Methods
4.3 Qualitative Evaluation
4.4 Ablation Analysis
5 Conclusions
References
Multi-scale Transformer with Decoder for Image Quality Assessment
1 Introduction
2 Related Work
2.1 Traditional Blind IQA
2.2 CNN-Based Blind IQA
2.3 ViT-Based Blind IQA
3 Proposed Method
3.1 Overall Architecture
3.2 Multi-scale Input
3.3 Attention Aggregation in Transformer Encoder
3.4 Decoder and Quality Score Generation
4 Experimental Results
4.1 Datasets and Evaluation Protocols
4.2 Implementation Details
4.3 Comparison of Quality Evaluation Results
4.4 Ablation Experiment
5 Conclusion
References
Low-Light Image Enhancement via Unsupervised Learning
1 Introduction
2 Related Work
2.1 Traditional Method
2.2 Deep Learning Method
3 Proposed Method
3.1 Vision Transformer Discriminator
3.2 Loss Function
4 Experiment
4.1 Datasets and Implementation Details.
4.2 Performance Evaluation
4.3 Ablation Study
5 Conclusion
References
GLCANet: Context Attention for Infrared Small Target Detection
1 Introduction
2 Related Work
2.1 Infrared Small Target Detection
2.2 Global Contextual Information
2.3 Local Contextual Information
3 Method
3.1 Overall Architecture
3.2 Global Context Extraction Module
3.3 Local Context Attention Module
4 Experiment
4.1 Datasets and Evaluation Metrics
4.2 Implementation Details
4.3 Quantitative Results
4.4 Visual Results
4.5 Ablation Study
5 Conclusion
References
Fast Point Cloud Registration for Urban Scenes via Pillar-Point Representation
1 Introduction
2 Related Works
3 Methodology
3.1 Pillar-Point Based Feature Extractor
3.2 Hierarchical Matching Scheme
3.3 Pose Estimator
3.4 Loss Function
4 Experiments
4.1 Implementation Details
4.2 Results on KITTI and NuScenes
4.3 Generalization to Apollo Southbay Dataset
4.4 Ablation Study
5 Conclusion
References
PMPI: Patch-Based Multiplane Images for Real-Time Rendering of Neural Radiance Fields
1 Introduction
2 Related Work
2.1 Neural Implicit Representations for View Synthesis
2.2 Representations of Multiplane Images
3 Representation of Patch-Based Multiplane Images
4 Training of Adaptive PMPI
4.1 Initialization of Patches
4.2 Learning Appearance and Geometry
4.3 Updating Structure of PMPI
5 Real-Time Rendering with Customized CUDA Kernel
6 Experiments
6.1 Training Details of Our Method
6.2 Comparisons
6.3 Ablation Study
7 Conclusions
References
EFPNet: Effective Fusion Pyramid Network for Tiny Person Detection in UAV Images
1 Introduction
2 Related Works
3 The Proposed Method
3.1 Overview of the Proposed EFPNet
3.2 Multi-dimensional Attention Module
3.3 Effective Feature Fusion Module
4 Experiments and Results
4.1 Experimental Settings
4.2 Visualization Analysis
4.3 Comparison to State-of-the-arts
4.4 Ablation Experiments
5 Conclusions
References
End-to-End Object-Level Contrastive Pretraining for Detection via Semantic-Aware Localization
1 Introduction
2 Related Work
2.1 Self-supervised Learning for Classification
2.2 Self-supervised Learning for Object Detection
2.3 Selective Object COntrastive Learning (SoCo)
3 Method
3.1 Semantic-Aware Localization
3.2 Center-Suppressed Sampling
3.3 Multiple Crop
4 Experiment
4.1 Pretraining Settings
4.2 Finetuning Settings
4.3 Training Time and Space Cost
4.4 Performance Comparison
4.5 Ablation Study
5 Conclusion
References
PointerNet with Local and Global Contexts for Natural Language Moment Localization
1 Introduction
2 Our Approach
2.1 Word Recurrence for Multimodal Clip Features
2.2 Clip Recurrence and Global Video Context
2.3 PointerNet-Based Moment Localization
2.4 Training
3 Experiments
3.1 Ablation Study
3.2 Comparison with State-of-the-art
4 Conclusion
References
Self-supervised Meta Auxiliary Learning for Actor and Action Video Segmentation from Natural Language
1 Introduction
2 Our Approach
2.1 Feature Extraction Network
2.2 Primary Segmentation Network
2.3 Auxiliary Language Reconstruction Network
2.4 Meta Auxiliary Training
3 Experiments
3.1 Ablation Study
3.2 Comparison with the State-of-the-art
4 Conclusion
References
RsMmFormer: Multimodal Transformer Using Multiscale Self-attention for Remote Sensing Image Classification
1 Introduction
2 Related Works
3 Methodology
3.1 Overall Architecture
3.2 Multi-scale Multi-Head Self-Attention (MSMHSA)
4 Experiments and Analysis
4.1 Experimental Setup
4.2 Quantitative Analysis
4.3 Ablation Study
4.4 Visualization
5 Conclusion
References
Fashion Label Relation Networks for Attribute Recognition
1 Introduction
2 Related Work
3 Methodology
3.1 Framework
3.2 Learning Objective
4 Experiment
4.1 Benchmark Dataset and Evaluation Metrics
4.2 Implementation Details
4.3 Comparison with the Benchmarking Methods
4.4 Performance Analysis
4.5 Results on Clothes Retrieval Datasets
5 Conclusion
References
A Modified Fuzzy Markov Random Field Incorporating Multiple Features for Liver Tumor Segmentation
1 Introduction
2 Proposed Method
2.1 Feature Extraction
2.2 The Modified Fuzzy Markov Random Field Model
2.3 Post-processing
3 Experimental Results
3.1 Dataset and Evaluation Measures
3.2 Experimental Details
3.3 Results and Discussion
4 Conclusion
References
Weakly Supervised Optical Remote Sensing Salient Object Detection Based on Adaptive Discriminative Region Suppression
1 Introduction
2 Related Work
2.1 Salient Object Detection in Optical Remote Sensing Images
2.2 Weakly Supervised Salient Object Detection
3 Method
3.1 Overall Structure
3.2 Local Activation Suppression Module
3.3 Adaptive Fusion Module
3.4 Multi-filter Directive Network
4 Experiments
4.1 Implementation Details
4.2 Datasets and Evaluation Metrics
4.3 Comparison with State-of-the-Art Methods
4.4 Ablation Studies
5 Conclusion
References
SPCTNet: A Series-Parallel CNN and Transformer Network for 3D Medical Image Segmentation
1 Introduction
2 Method
2.1 Architecture
2.2 Transformer Block
2.3 Multi-scale Feature Fusion (MSF)
2.4 Loss Function
3 Experiments
3.1 Datasets
3.2 Experimental Settings and Evaluation Metrics
3.3 Ablation Study
3.4 Quantitative Evaluation
3.5 Qualitative Evaluation
4 Conclusion
References
LANet: A Single Stage Lane Detector with Lightweight Attention
1 Introduction
2 Related Work
3 Proposed Method
3.1 Anchor Representation
3.2 Backbone and Feature Pooling
3.3 Anchor-Frame Attention
3.4 Prediction
3.5 Non-maximum Supression (NMS)
3.6 Model Training
4 Experiments
4.1 Tusimple
4.2 CULane
4.3 Ablation Study
5 Conclusion
References
Visible and NIR Image Fusion Algorithm Based on Information Complementarity
1 Introduction
2 Related Work
3 The Proposed Algorithm
3.1 Two-Scale Guided Image Decomposition
3.2 Inter-band Information Complementarity Map Estimation
3.3 Information Complementary Weight Model
4 Experimental Results
4.1 Objective Comparison
4.2 Subject Comparison
5 Conclusion
References
Data Mining
End-to-End Optimization of Quantization-Based Structure Learning and Interventional Next-Item Recommendation
1 Introduction
2 Related Works
3 Methodology
3.1 Problem Formulation
3.2 Causal Structure Learning in Recommendation
3.3 Quantization-Based Structure Learning
3.4 End-to-End Optimization
4 Experiments
4.1 Experimental Setup
4.2 Experiments Results
4.3 Parameter Analysis
4.4 Ablation Study
4.5 OOD Generalization
5 Conclusion
A Appendix
A.1 Experimental Setup
References
Multi-trends Enhanced Dynamic Micro-video Recommendation
1 Introduction
2 Our Approach
2.1 Problem Formulation
2.2 Overview
2.3 Implicit User Network
2.4 Multi-trend Routing
2.5 Multi-level Time Attention Mechanism
2.6 Prediction
3 Experiments
3.1 Dataset
3.2 Implementation Details
3.3 Evaluation Metrics
3.4 Competitors
3.5 Results
3.6 Recommendation Diversity
4 Conclusion
References
Parameters Efficient Fine-Tuning for Long-Tailed Sequential Recommendation
1 Introduction
2 Related Work
2.1 Long-Tail
2.2 Gradient Surgery
3 Method
3.1 Preliminaries
3.2 Gradient Aggregation
3.3 Plugin Network
4 Experiments
4.1 Experiment Settings
4.2 Experiments and Results
5 Conclusion
A Pseudo Code
B Experiments
B.1 Experiments Settings
B.2 Results
References
Heterogeneous Link Prediction via Mutual Information Maximization Between Node Pairs
1 Introduction
2 Related Work
2.1 Heterogeneous Graph Embedding
2.2 Link Prediction
3 Preliminaries
4 Methodology
5 Experiments
5.1 Experiment Settings
5.2 Results on Link Prediction
5.3 Ablation Studies
5.4 Parameters Experiments
6 Conclusion
References
Explainability, Understandability, and Verifiability of AI
ADAPT: Action-Aware Driving Caption Transformer
1 Introduction
2 Method
2.1 Overview
2.2 Model Design
3 Experiment
3.1 Implementation Details
3.2 Main Results
3.3 Accelerate the Inference Process
4 Conclusion
References
Structural Recognition of Handwritten Chinese Characters Using a Modified Part Capsule Auto-encoder
1 Introduction
2 Related Work
3 Methodology
3.1 Overall Framework
3.2 Primitive Extraction
3.3 Stroke Aggregation
3.4 Character Recognition
4 Experiments
4.1 Implementation Details
4.2 Datasets
4.3 Effects of Primitive and Stroke Extraction
4.4 Performance of Chinese Character Recognition
4.5 Ablation Study
5 Conclusion
References
Natural Language Processing
Sequential Style Consistency Learning for Domain-Generalizable Text Recognition
1 Introduction
2 Method
2.1 Base Network
2.2 Sequential Style Consistency Learning
2.3 Training and Inference
3 Experiments
3.1 Dataset and Metrics
3.2 Implementation Details
3.3 Model Selection
3.4 Comparison Baselines
3.5 Comparison Results
3.6 Ablation Studies
4 Conclusion
References
MusicGAIL: A Generative Adversarial Imitation Learning Approach for Music Generation
1 Introduction
2 Musical Data Representation and Preprocessing
2.1 Interactive Duet Model
2.2 Pitch and Duration Encodings
3 Generative Adversarial Imitation Learning
3.1 MusicGAIL Framework
3.2 Melodic Generator
3.3 Style-Discriminator
4 Experimental Results
4.1 Dataset
4.2 The Training Process of MusicGAIL
4.3 Comparison and Evaluation
5 Conclusion
References
Unsupervised Traditional Chinese Herb Mention Normalization via Robustness-Promotion Oriented Self-supervised Training
1 Introduction
2 Approach
2.1 Overall Result
2.2 Ablation Study
2.3 Analysis
3 Conclusion
References
Feature Fusion Gate: Improving Transformer Classifier Performance with Controlled Noise
1 Introduction
2 Related Works
2.1 The Gating Mechanism of LSTM
2.2 Mixup
3 Proposed Methodology
4 Experiments and Results
4.1 Benchmark Datasets and Models
4.2 Baselines
4.3 Experimental Settings
4.4 Overall Results
5 Conclusion and Future Work
References
Multi-round Dialogue State Tracking by Object-Entity Alignment in Visual Dialog
1 Introduction
2 Related Work
3 Model
4 Experiment
5 Conclusions
References
Multi-modal Dialogue State Tracking for Playing GuessWhich Game
1 Introduction
2 Related Work
3 Model
4 Experiment and Evaluation
5 Conclusion
References
Diagnosis Then Aggregation: An Adaptive Ensemble Strategy for Keyphrase Extraction
1 Introduction
2 Related Work
3 Problem Definition
4 Adaptive Ensemble Strategy via Cognitive Diagnosis
4.1 Cognitive Diagnose for Keyphrase Extraction Algorithms
4.2 Adaptive Ensemble Strategy
5 Experiments
5.1 Experimental Setup
5.2 Evaluation Metrics
5.3 Experimental Results
6 Conclusion
References
Author Index