
Advances in Computational Vision and Robotics
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Advances in Computational Vision and Robotics contains research papers from diverse field of engineering, computer science, social and bio-medical science. This book contains various research articles from the following domain:
i. Pattern recognition and Robotic Vision.
ii. Artificial Intelligence and Deep Learning application.
iii. Big Data Application in Robotics.
iv. Deep Learning and Neural Network.
Authors from the area of Particle Swarm Optimization, Defect Detection, Gesture Information Collection, Image Processing and Remote Sensing, Melody Recognition, Convolution Neural Network and Satellite Image processing etc. have contributed their research outcomes.More details
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Additional editions

Content
- Intro
- ICCVR-2023 Conference Committee
- Preface
- Acknowledgements
- About This Book
- Contents
- About the Editors
- Part I Pattern Recognition and Robotic Vision
- 1 Design of Piano Automatic Accompaniment System Based on Markov Model
- 1.1 Introduction
- 1.2 Methodology
- 1.2.1 Related Theory of Algorithmic Composition
- 1.2.2 Automatic Piano Accompaniment System Based on HMM
- 1.3 Result Analysis and Discussion
- 1.4 Conclusions
- References
- 2 3D Visual Design of Music Based on Multi-audio Features
- 2.1 Introduction
- 2.2 Methodology
- 2.2.1 Audio Visualization Method
- 2.2.2 Multi-audio Feature Extraction of Music
- 2.3 Result Analysis and Discussion
- 2.4 Conclusions
- References
- 3 Construction of Humming Music Retrieval Model Based on Particle Swarm Optimization
- 3.1 Introduction
- 3.2 Related Music Knowledge in Humming Music Retrieval
- 3.2.1 Elements of Sound
- 3.2.2 The Relationship and Difference Between Voice Signals and Humming Music Signals
- 3.3 Constructing a Humming Music Retrieval Model
- 3.3.1 Basic Framework
- 3.3.2 Model Application
- 3.4 Conclusions
- References
- 4 Research on Audio Processing Method Based on 3D Technology
- 4.1 Introduction
- 4.2 Audio Processing Method Based on 3D Technology
- 4.3 Result Analysis and Discussion
- 4.4 Conclusions
- References
- 5 Design and Optimization of Point Cloud Registration Algorithm Based on Stereo Vision and Feature Matching
- 5.1 Introduction
- 5.2 Research Method
- 5.2.1 Stereo Vision Model
- 5.2.2 Feature Matching Based on Stereo Vision
- 5.3 Experiment and Analysis
- 5.4 Conclusion
- References
- 6 Design of 3D Point Cloud Real-Time Cloud Matching Algorithm Based on Multi-scale Feature Extraction
- 6.1 Introduction
- 6.2 Research Method
- 6.2.1 Multiscale Feature Extraction
- 6.2.2 Real-Time Cloud Matching Acceleration of 3D Point Cloud
- 6.3 Experimental Analysis
- 6.4 Conclusion
- References
- 7 Design of Digital Music Copyright Protection System Based on Blockchain Technology
- 7.1 Introduction
- 7.2 Research Method
- 7.2.1 System Overall Design
- 7.2.2 Key Technology Realization
- 7.3 Result Analysis
- 7.4 Conclusion
- References
- 8 Personalized Music Recommendation Model Based on Collaborative Filtering Algorithm and K-Means Clustering
- 8.1 Introduction
- 8.2 Collaborative Filtering Algorithm
- 8.3 Design of Personalized Music Recommendation Model
- 8.4 Implementation of a Personalized Music Recommendation Model
- 8.4.1 Personalized Music Model Recommendation Process
- 8.4.2 Result Analysis
- 8.5 Conclusions
- References
- 9 Simulation of Fuzzy Calculation Model of Music Emotion Based on Improved Genetic Algorithm
- 9.1 Introduction
- 9.2 Simulation Research on Fuzzy Computing Model of Music Emotion
- 9.2.1 Quantitative Research on Musical Emotion
- 9.2.2 Construction of a Fuzzy Computing Model for Music Emotion
- 9.3 Simulation of Fuzzy Calculation Model of Music Emotion Based on Improved GA
- 9.3.1 Improved GA Model
- 9.3.2 Analysis of Experimental Results
- 9.4 Conclusion
- References
- 10 Design and Implementation of Piano Performance Automatic Evaluation System Based on Support Vector Machine
- 10.1 Introduction
- 10.2 Methodology
- 10.2.1 Related Technical Basis
- 10.2.2 Design and Implementation of Automatic Assessment System for Piano Performance
- 10.3 Result Analysis and Discussion
- 10.4 Conclusions
- References
- 11 Simulation of Music Personalized Recommendation Model Based on Collaborative Filtering
- 11.1 Introduction
- 11.2 Simulation of Music Personalized Recommendation Model
- 11.2.1 Basic Theory of Music Recommendation System
- 11.2.2 Personalized Recommendation System and Related Technologies
- 11.3 Simulation of Music Personalized Recommendation Model Based on CF
- 11.3.1 Collaborative Filtering Algorithm
- 11.3.2 Analysis of Experimental Results
- 11.4 Conclusion
- References
- 12 Design and Optimization of Image Recognition and Classification Algorithm Based on Machine Learning
- 12.1 Introduction
- 12.2 Image Classification and Retrieval Method Based on Image Visual Features
- 12.2.1 Theoretical Basis of Machine Learning Recognition Algorithm
- 12.2.2 Research on Virtual Sample Algorithm in Image Recognition
- 12.3 Image Retrieval Method Combining Machine Learning with Image Visual Features
- 12.3.1 Image Recognition Advertising Classification Algorithm Model
- 12.3.2 Experimental Analysis Results
- 12.4 Conclusion
- References
- 13 Design of Path Planning Algorithm for Intelligent Robot Based on Chaos Genetic Algorithm
- 13.1 Introduction
- 13.2 Concept and Principle of Chaotic Genetic Algorithm
- 13.3 Path Planning Method
- 13.3.1 Coding Based on Geographic Information
- 13.3.2 Simplification of Robot Control Parameters
- 13.4 Simulation Study
- 13.5 Conclusions
- References
- 14 Design and Development of Rail Transit Overhead Contact Line Monitoring System Based on Image Processing
- 14.1 Introduction
- 14.2 Related Concepts
- 14.2.1 Catenary
- 14.2.2 Image Processing Technology
- 14.3 System Design
- 14.3.1 Overall Scheme Design
- 14.3.2 Monitoring Preprocessing Module
- 14.3.3 Monitoring Terminal Energy Consumption Analysis
- 14.4 System Implementation
- 14.4.1 Monitoring Terminal Energy-Saving Mode
- 14.4.2 System Performance Test
- 14.5 Conclusion
- References
- 15 Ultrasonic Signal Processing Method for Transformer Oil Based on Improved EMD
- 15.1 Introduction
- 15.2 Tests and Methods
- 15.2.1 Ultrasonic Testing
- 15.2.2 Ultrasonic Signal Processing Method Based on Improved EMD
- 15.3 Results and Discussion
- 15.4 Conclusion
- References
- 16 Research on UHV Transmission Line Selection Strategy Aided by Satellite Remote Sensing Image
- 16.1 Introduction
- 16.2 Research Method
- 16.2.1 Data Processing
- 16.2.2 Precise Correction of RS Image
- 16.2.3 Transmission Line Path Optimization
- 16.3 Accuracy Analysis
- 16.4 Conclusions
- References
- 17 Research on the Evaluation of the Teaching Process of Public Physical Education in Universities Based on Markov Model
- 17.1 Introduction
- 17.2 Research Method
- 17.2.1 Establishment of Evaluation Index System
- 17.2.2 Markov Model
- 17.3 An Example of Evaluation of Public PE Class Teaching Process
- 17.4 Conclusion
- References
- Part II Artificial Intelligence and Deep Learning Application
- 18 Simulation Design of Matching Model Between Action and Music Tempo Characteristics Based on Artificial Intelligence Algorithm
- 18.1 Introduction
- 18.2 Methodology
- 18.2.1 Basic Technology of Artificial Intelligence
- 18.2.2 Construction of Matching Model Between Dance Actions and Music Tempo Characteristics
- 18.3 Result Analysis and Discussion
- 18.4 Conclusions
- References
- 19 Design and Optimization of Frequency Identification Algorithm for Monomelody Musical Instruments Based on Artificial Intelligence Technology
- 19.1 Introduction
- 19.2 Methodology
- 19.2.1 Overall Structure of Audio Features
- 19.2.2 Frequency Identification Algorithm of Musical Instruments in Single Melody Music
- 19.3 Result Analysis and Discussion
- 19.4 Conclusion
- References
- 20 Design of Intelligent Evaluation Algorithm for Matching Degree of Music Words and Songs Based on Grey Clustering
- 20.1 Introduction
- 20.2 Methodology
- 20.2.1 Representation and Extraction of Melody Features
- 20.2.2 Digital Music Signal Denoising Algorithm
- 20.3 Result Analysis and Discussion
- 20.4 Conclusion
- References
- 21 Construction of Evaluation Model for Singing Pronunciation Quality Based on Artificial Intelligence Algorithms
- 21.1 Introduction
- 21.2 Two Evaluation Systems Based on Artificial Intelligence Algorithm
- 21.2.1 Objective Evaluation Based on the Extraction of Evaluation Parameters of Singing Voice
- 21.2.2 An Objective Evaluation Mechanism Based on Subjective Evaluation Criteria Quantification
- 21.3 Evaluation Model of Singing Pronunciation Quality
- 21.4 Analysis of Experimental Results
- 21.5 Conclusions
- References
- 22 Design and Optimization of Intelligent Composition Algorithm Based on Artificial Intelligence
- 22.1 Introduction
- 22.2 Model and Algorithm Design
- 22.2.1 Music Feature Extraction
- 22.2.2 Intelligent Composition Algorithm
- 22.3 Result Analysis and Discussion
- 22.4 Conclusions
- References
- 23 Design of Computer-Aided Music Generation Model Based on Artificial Intelligence Algorithm
- 23.1 Introduction
- 23.2 Research Method
- 23.2.1 Data Preprocessing
- 23.2.2 Implementation of AI Algorithm
- 23.3 Experimental Analysis
- 23.4 Conclusion
- References
- 24 Construction of Electronic Music Classification Model Based on Machine Learning and Deep Learning Algorithm
- 24.1 Introduction
- 24.2 Constructing EM Classification Model
- 24.2.1 Overall Structural Design
- 24.2.2 Multi Layer Perceptual Feature Classification Processing
- 24.3 Construction of EM Classification Model Based on ML and DL Algorithms
- 24.3.1 NN Algorithm Model for ML Optimization
- 24.3.2 Analysis of Experimental Results
- 24.4 Conclusion
- References
- 25 Design of Piano Automatic Accompaniment System Based on Artificial Intelligence Algorithm
- 25.1 Introduction
- 25.2 Research Method
- 25.2.1 Design of Piano Automatic Accompaniment Algorithm
- 25.2.2 System Structure Design
- 25.3 Result Analysis
- 25.4 Conclusion
- References
- 26 The Importance of the Application of Intelligent Management System to Laboratory Management in Colleges and Universities
- 26.1 Introduction
- 26.2 Composition of Intelligent Management System
- 26.3 Advantages and Workflow Analysis of Laboratory Intelligent Management System
- 26.4 Application of Intelligent Management System in Laboratory Management in Colleges and Universities
- 26.5 Conclusion
- References
- 27 Design of Defect Detection Algorithm for Printed Packaging Products Based on Computer Vision
- 27.1 Introduction
- 27.2 Methodology
- 27.2.1 Printing Packaging Defect Detection
- 27.2.2 Printing Defect Detection Algorithm
- 27.3 Result Analysis and Discussion
- 27.4 Conclusions
- References
- 28 Leap Motion Gesture Information Collection and Gesture Interaction System Construction
- 28.1 Introduction
- 28.2 Methodology
- 28.2.1 Collection and Processing of Gesture Data
- 28.2.2 Gesture Recognition Model of Interactive System
- 28.3 Result Analysis and Discussion
- 28.4 Conclusion
- References
- 29 Optimization of Moving Object Tracking Algorithm Based on Computer Vision and Vision Sensor
- 29.1 Introduction
- 29.2 Methodology
- 29.2.1 Computer Vision and Moving Object Detection
- 29.2.2 Moving Target Tracking Algorithm
- 29.3 Result Analysis and Discussions
- 29.4 Conclusion
- References
- 30 Simulation Experiment of DPCM Compression System for High Resolution Multi-spectral Remote Sensing Images
- 30.1 Introduction
- 30.2 Research Method
- 30.2.1 WT and Bit Plane Coding
- 30.2.2 Segmentation DPCM Compression Algorithm
- 30.3 Simulation Experiment Analysis
- 30.4 Conclusions
- References
- Part III Big Data Application in Robotics
- 31 Construction of Music Classification and Detection Model Based on Big Data Analysis and Genetic Algorithm
- 31.1 Introduction
- 31.2 Construction of Music Classification and Detection Model
- 31.2.1 Related Technologies and Implementation Methods of Music Retrieval
- 31.2.2 Construction of Music Classification Model
- 31.3 Analysis of Music Classification and Detection Construction Based on Big Data Analysis and Genetic Algorithm
- 31.3.1 Model Simulation Base on Big Data Analysis and Genetic Algorithm
- 31.3.2 Analysis of Experimental Results
- 31.4 Conclusion
- References
- 32 Simulation of Electronic Music Signal Identification Model Based on Big Data Algorithm
- 32.1 Introduction
- 32.2 Music Signal Feature Recognition
- 32.3 Result Analysis and Discussion
- 32.4 Conclusion
- References
- 33 Design of Interactive Teaching Music Intelligent System Based on AI and Big Data Analysis
- 33.1 Introduction
- 33.2 Methodology
- 33.2.1 Relevant Theoretical and Technical Basis
- 33.2.2 Construction of Reciprocal Teaching Music Intelligent System
- 33.3 Result Analysis and Discussion
- 33.4 Conclusions
- References
- 34 Research on Music Database Construction Combining Big Data Analysis and Machine Learning Algorithm
- 34.1 Introduction
- 34.2 Methodology
- 34.2.1 Big Data Analysis and Machine Learning Algorithms
- 34.2.2 Construction of Music Database and Recommendation System
- 34.3 Result Analysis and Discussion
- 34.4 Conclusions
- References
- 35 Construction and Optimization Design of Pop Music Database Based on Big Data Technology
- 35.1 Introduction
- 35.2 Research Method
- 35.2.1 Overall Design of Pop Music Database
- 35.2.2 Database Query Optimization
- 35.3 Simulation Experiment
- 35.4 Conclusion
- References
- 36 The Application of Big Data in the Construction of Modern Vocal Education Score Database
- 36.1 Introduction
- 36.2 Basic Content of Music Score Database Construction
- 36.2.1 Construction of Music Score Database
- 36.2.2 The Concrete Method of Music Score Database Construction
- 36.3 Application of BD in the Construction of Music Score Database for Modern Vocal Pedagogy
- 36.3.1 Improved Parallel Association Rule Mining Algorithm Based on Vocal Music Education Data
- 36.3.2 Analysis of Experimental Results
- 36.4 Conclusion
- References
- 37 Application of Big Data Analysis Technology in Music Style Recognition and Classification
- 37.1 Introduction
- 37.2 Methodology
- 37.2.1 Digital Management of Music Audio and Video Driven by Big Data
- 37.2.2 Music Style Recognition and Classification Algorithm
- 37.3 Result Analysis and Discussion
- 37.4 Conclusion
- References
- 38 Construction of Piano Music Recognition System Based on Big Data Algorithm
- 38.1 Introduction
- 38.2 Basic Characteristics of Piano Music and Music Signal Preprocessing
- 38.2.1 Overview of Piano Music Characteristics
- 38.2.2 Piano Music Signal Preprocessing
- 38.3 System Design
- 38.4 System Test and Result Analysis
- 38.5 Conclusions
- References
- 39 Design of Music Recommendation Algorithm Based on Big Data Analysis and Cloud Computing
- 39.1 Introduction
- 39.2 Research Method
- 39.2.1 User Behavior and User Portrait Modeling
- 39.2.2 Implementation of Music Recommendation Algorithm
- 39.3 Experimental Analysis
- 39.4 Conclusion
- References
- 40 Simulation of Sports Damage Assessment Model Based on Big Data Analysis
- 40.1 Introduction
- 40.2 Research Method
- 40.2.1 Establishment of Risk Factors of Sports Injury
- 40.2.2 Construction of Sports Injury Assessment Model
- 40.3 Simulation Analysis
- 40.4 Conclusion
- References
- 41 Construction of Purchase Intention Model of Digital Music Products Based on Data Mining Algorithm
- 41.1 Introduction
- 41.2 Methodology
- 41.2.1 Features of Digital Music Products
- 41.2.2 Digital Music Product Purchase Prediction Model
- 41.3 Result Analysis and Discussion
- 41.4 Conclusion
- References
- 42 English Learning Analysis and Individualized Teaching Strategies Based on Big Data Technology
- 42.1 Introduction
- 42.2 Introduction of Educational Big Data and Related Technologies
- 42.2.1 Big Data for Education
- 42.2.2 Education Data Mining
- 42.2.3 The Relationship Between English Teaching and Big Data
- 42.3 Application of Data Mining Technology in Learning Analysis
- 42.3.1 Learning Analysis Techniques
- 42.3.2 Construction of Learning Analysis Technology Model
- 42.4 Application of Data Mining Technology in Personalized English Teaching
- 42.4.1 Teaching Design
- 42.4.2 Use Learning Analysis Technology to Analyze Personalized Data
- 42.4.3 Personalized Data Feedback
- 42.5 English Teaching Practice
- 42.5.1 Research Object Selection and Analysis
- 42.5.2 Analysis of the Effect of Personalized Learning Supported by WeChat Network Platform
- 42.5.3 Discussion of Practical Results
- 42.6 Conclusion
- References
- 43 Research on Distributed Storage and Efficient Distribution Technology of High Resolution Optical Remote Sensing Data
- 43.1 Introduction
- 43.2 Related Work
- 43.3 Methodology
- 43.4 Result Analysis and Discussion
- 43.5 Conclusions
- References
- 44 Research and Application of Digital Modeling Technology Based on Multi-source Data of Power Grid
- 44.1 Introduction
- 44.2 Related Work
- 44.3 Research on Digital Modeling Technology Based on Multi-source Data of Power Grid
- 44.3.1 Power Grid Multi-source Data Perception and Extraction
- 44.3.2 Digital Modeling of Multi-source Data in Power Grids
- 44.4 Application of Digital Model Based on Multi-source Data of Power Grid
- 44.4.1 Electricity Compliance Inspection Based on Digital Power Model
- 44.4.2 Application of Power Equipment State Feature Analysis Based on Digital Power Model
- 44.5 Application Results
- References
- 45 Construction of Music Popular Trend Prediction Model Based on Big Data Analysis
- 45.1 Introduction
- 45.2 Description and Preprocessing of Music Data
- 45.2.1 Data Description
- 45.2.2 Data Analysis
- 45.3 Construction and Analysis of Numerical Prediction Model
- 45.3.1 Prediction Model of Music Pop Trend
- 45.3.2 Prediction and Analysis of Music Trend Based on Big Data Analysis
- 45.4 Conclusions
- References
- Part IV Deep Learning and Neural Network
- 46 Construction of Personalized Music Emotion Classification Model Based on BP Neural Network Algorithm
- 46.1 Introduction
- 46.2 Analysis and Extraction of Music Emotional Eigenvalues
- 46.2.1 MIDI Audio File Analysis
- 46.2.2 Main Track Recognition
- 46.2.3 Feature Extraction of MIDI Audio Files
- 46.3 Construction of Music Emotion Classification Model Based on BP Neural Network
- 46.4 Analysis of Experimental Results
- 46.5 Conclusions
- References
- 47 Music Main Melody Recognition Algorithm Based on BP Neural Network Model
- 47.1 Introduction
- 47.2 Methodology
- 47.2.1 Digital Processing of Acoustic and Speech Signals
- 47.2.2 Music Main Melody Recognition Algorithm
- 47.3 Result Analysis and Discussion
- 47.4 Conclusions
- References
- 48 Design of Piano Score Difficulty Level Recognition Algorithm Based on Artificial Neural Network Model
- 48.1 Introduction
- 48.2 Methodology
- 48.2.1 Piano Audio Signal Recognition
- 48.2.2 Algorithm Design of Piano Score Difficulty Level Recognition
- 48.3 Result Analysis and Discussion
- 48.4 Conclusions
- References
- 49 Design and Optimization of Improved Recognition Algorithm for Piano Music Based on BP Neural Network
- 49.1 Introduction
- 49.2 Methodology
- 49.2.1 The Main Task of Music Recognition
- 49.2.2 Improvement of BPNN in Piano Music Recognition
- 49.3 Result Analysis and Discussion
- 49.4 Conclusions
- References
- 50 Design of Piano Music Type Recognition Algorithm Based on Convolutional Neural Network
- 50.1 Introduction
- 50.2 Methodology
- 50.2.1 Related Technical Basis
- 50.2.2 Design of Piano Music Type Recognition Algorithm
- 50.3 Result Analysis and Discussion
- 50.4 Conclusions
- References
- 51 Application of Emotion Recognition Technology Based on Support Vector Machine Algorithm in Interactive Music Visualization System
- 51.1 Introduction
- 51.2 Research Method
- 51.2.1 Emotion Recognition Based on SVM Algorithm
- 51.2.2 Realization of Interactive Music Visualization System
- 51.3 Result Analysis
- 51.4 Conclusion
- References
- 52 Research on Image Classification Algorithm of Film and Television Animation Based on Generative Adversarial Network
- 52.1 Introduction
- 52.2 Methodology
- 52.2.1 Image Characteristics of Contemporary Film and Television Animation
- 52.2.2 Video Animation Image Classification Algorithm Based on GAN
- 52.3 Result Analysis and Discussion
- 52.4 Conclusion
- References
- 53 Study on Monitoring Forest Disturbance During Power Grid Construction Based on BJ-3 Satellite Image
- 53.1 Introduction
- 53.2 Study Area and Data
- 53.3 Study Method
- 53.3.1 High-Resolution Image Segmentation
- 53.3.2 Feature Selection
- 53.3.3 Forest Information Extraction and Interference Monitoring
- 53.4 Result Analysis
- 53.5 Conclusion
- References
- 54 Transformative Advances in English Learning: Harnessing Neural Network-Based Speech Recognition for Proficient Communication
- 54.1 Introduction
- 54.2 Related Research
- 54.2.1 Introduction of Neural Network
- 54.2.2 Introduction of Speech Recognition in Oral English Learning
- 54.3 Simulation and Experiment of Speech Recognition in Oral English Learning Based on Neural Network
- 54.3.1 Introduction
- 54.3.2 Evaluation Metrics for Assessing Speech Recognition Performance in Oral English Learning
- 54.3.3 Experimental Results and Analysis
- 54.4 The Role of Neural Network-Based Speech Recognition in Shaping the Future of Oral English Learning
- 54.5 Conclusion
- References
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