Computer Vision and Machine Intelligence Paradigms for SDGs: Select Proceedings of ICRTAC-CVMIP 2021

✍ Scribed by R. Jagadeesh Kannan, Sabu M. Thampi, Shyh-Hau Wang

• Publisher: Springer
• Year: 2023
• Tongue: English
• Leaves: 339
• Series: Lecture Notes in Electrical Engineering, 967
• Edition: 1st ed. 2023
• Category: Library

✦ Synopsis

This book constitutes refereed proceedings of the 4th International Conference on Recent Trends in Advanced Computing - Computer Vision and Machine Intelligence Paradigms for Sustainable Development Goals. This book covers novel and state-of-the-art methods in computer vision coupled with intelligent techniques including machine learning, deep learning, and soft computing techniques. The contents of this book will be useful to researchers from industry and academia. This book includes contemporary innovations, trends, and concerns in computer vision with recommended solutions to real-world problems adhering to sustainable development from researchers across industry and academia. This book serves as a valuable reference resource for academics and researchers across the globe.

✦ Table of Contents

Preface
Contents
Editors and Contributors
PTZ-Camera-Based Facial Expression Analysis using Faster R-CNN for Student Engagement Recognition
1 Introduction
2 Related Work
2.1 Contribution and Objective
3 Methodology
3.1 Face Detection using YOLO Detector
3.2 Detection of Landmark Points using Ensemble of Robust Constrained Local Models (CLM)
3.3 Affine Transformation
3.4 Face Expression Recognition using Faster R-CNN (Faster Regions with Convolutional Neural Network)
4 Results and Discussion
4.1 Performance Analysis
5 Conclusion
References
Convergence Perceptual Model for Computing Time Series Data on Fog Environment
1 Introduction
1.1 Goals Aimed at the Convergence Fog Model
1.2 Fog for Time-Series Computing
1.3 Proposed Convergence Perceptual Architecture
1.4 Perceptual Layer on CPM
2 Conclusion
References
Localized Super Resolution for Foreground Images Using U-Net and MR-CNN
1 Introduction
2 Literature Survey
3 Proposed Architecture
4 Implementation and Training
4.1 Dataset and Augmentation
4.2 Model Architecture
4.3 Loss Function and Optimizer
4.4 Training
5 Evaluation Metrics
5.1 PSNR—Peak Signal-To-Noise Ratio
5.2 SSIM—Structural Similarity Index
5.3 Universal Image Quality Index
6 Results and Discussion
7 Conclusion and Future Work
References
SMS Spam Classification Using PSO-C4.5
1 Introduction
2 Problem Statement
3 Research Objective
4 Review of Literature
4.1 Review of Text-Processing
4.2 Review on Feature Extraction
4.3 Review on Feature Selection
4.4 Review on Classifiers
5 Research Contribution
6 Data Collection and Data Sampling
7 Experimental Results
8 Conclusion and Future Enhancement
References
Automated Sorting, Grading of Fruits Based on Internal and External Quality Assessment Using HSI, Deep CNN
1 Introduction
2 Related Works
3 Overview of Proposed Idea
3.1 Preprocessing
3.2 Segmentation
3.3 CNN Model Development
4 Experimental Results and Discussion
4.1 Experimental Setup
4.2 Performance Measures
4.3 Experimental Results
5 Conclusion
References
Pest Detection Using Improvised YOLO Architecture
1 Introduction
2 Literature Review
2.1 Pest Detection Methods
2.2 Pest Classification Methods
3 YOLO V3 Architecture
4 Improvised YOLO V3 Architecture
5 Results and Discussions
6 Conclusion
References
Classification of Fungi Effected Psidium Guajava Leaves Using ML and DL Techniques
1 Introduction
2 Literature Survey
3 Overview of Database
4 Proposed Method/Model
4.1 Classification Using Deep Learning Techniques
5 Experimental Results
5.1 Experimental Results Using Deep Learning Techniques
6 Comparative Analysis
7 Conclusions
References
Deep Learning Based Recognition of Plant Diseases
1 Introduction
2 Literature Review
3 Scope
4 Methodology
4.1 Procedure
4.2 Library
5 Results and Findings
6 Discussion
7 Conclusion
8 Future Scope
9 Recommendation
References
Artificial Cognition of Temporal Events Using Recurrent Point Process Networks
1 Introduction
2 Recurrent Point Process Network
2.1 Recurrent Neural Network
2.2 Interoperability and Prediction Module
2.3 Point Processes Equations
3 Automated Data Relation Process
3.1 Model Creation
3.2 Training Phase
3.3 Testing Phase
3.4 Anomaly Detection
3.5 Visualization
4 Temporal Variation Samples
4.1 Synchronous Event
4.2 Asynchronous Event
5 Conclusion
References
Performance Analysis of Energy Efficient Video Transmission Using LEACH Based Protocol in WSN
1 Introduction
2 Related Work
3 Problem Statement and Our Contribution
4 LEACH Based Routing Protocol
5 Video Transmission Over WSN
6 Experimental Result
7 Conclusion
References
Hybridization of Texture Features for Identification of Bi-Lingual Scripts from Camera Images at Wordlevel
1 Introduction
2 Review of Literature
3 Proposed Method
3.1 Creation of LBP Image
3.2 Extraction of GLCM Feature from LBP Image
3.3 Extraction HOG Feature from LBP Image
3.4 Combined Feature Vector of GLCM and HOG from LBP Image
4 Experimental Results and Discussion
4.1 Results and Discussion
5 Conclusion
References
Advanced Algorithmic Techniques for Topic Prediction and Recommendation—An Analysis
1 Introduction
2 Proposed Model
2.1 Hashtag-Based Approach
2.2 Word Ranking Based Approach
2.3 Authority Weighting Based Approach
2.4 Background Tweet Detection-Based Approach
2.5 Short-Term Fluctuation Modeling Based Approach
3 Results and Discussion
4 Conclusion
References
Implementation of an Automatic EEG Feature Extraction with Gated Recurrent Neural Network for Emotion Recognition
1 Introduction
2 Related Study
3 Methodology
3.1 Preprocessing
3.2 Feature Extraction
3.3 Classifier
4 Results and Discussions
4.1 Dataset
4.2 Implementation
5 Conclusion
References
High Performance Classifier for Brain Tumor Detection Using Capsule Neural Network
1 Introduction
2 Methods
2.1 Convolutional Neural Network
2.2 Capsule Networks
3 Literature Survey
4 Proposed Model
4.1 Capsule Network Model Creation
4.2 Prediction
5 Proposed Algorithm
5.1 Prediction Through Flask Framework
6 Results and Discussions
6.1 Accuracy
6.2 Predicting Tumor
6.3 Training and Validation
7 Conclusion
References
Mining Suitable Symptoms to Identify Disease Using Apriori and NBC
1 Introduction
2 Review of Literature
3 Association Rule Mining
4 Proposed Work
4.1 Apriori Algorithm
5 Conclusion
References
Background Features-Based Novel Visual Ego-Motion Estimation
1 Introduction
1.1 Related Work
2 Algorithm
2.1 System Overview
2.2 Steerable Pyramid Transformation (SPT)
2.3 Keypoint Detection and Matching
2.4 Ransac
3 Experimental Results
4 Conclusion
References
Livspecs: Design and Implementation of Smart Specs for Hearing and Visually Challenged Persons
1 Introduction
2 Literature Survey
3 Proposed System
4 Result and Discussion
5 Conclusion
References
Self-balancing Robot Using Arduino and PID Controller
1 Introduction
2 Related Works
3 Proposed Methodology
3.1 Block Diagram of the Two-Wheeled Robot
3.2 Working Principle
3.3 Control Action
4 Results and Discussion
5 Conclusion
References
A Survey Based on Online Voting System Using Blockchain Technology
1 Introduction
2 Background
2.1 Overview of Computerized Voting System
2.2 Blockchain Technology
2.3 Analysis of Ethereum
3 Comparative Study of Blockchain-Based Electronic Voting Plans
4 Discussion
5 Conclusion and Future Work
References
Survey on Collaborative Filtering Technique for Recommender System Using Deep Learning
1 Introduction
2 Recommender Systems
2.1 Deep Learning-Based Recommendation Systems
2.2 Deep Collaborative Filtering Techniques
2.3 Datasets
3 Recommendation System Applications
4 Conclusion
References
A Survey on Power Consumption Indicator Using Machine Learning-Based Approach
1 Introduction
2 System Description
2.1 Power Limit Indicator System (PLIS)
2.2 PLIS Basic Flow
3 Review and Analysis of Power Consumption Systems
4 Conclusion
References
A Novel Hand Gesture Recognition for Aphonic People Using Convolutional Neural Network
1 Introduction
2 Proposed Methodology
2.1 Binarization
2.2 Contour Detection
2.3 Feature Extraction Using Sift Algorithm
2.4 Classification Using Convolutional Neural Network
3 Experimental Results
4 Conclusion and Future Enhancement
References
Comprehensive Analysis of Defect Detection Through Image Processing and Machine Learning for Photovoltaic Panels
1 Introduction
1.1 Photovoltaic Panels
1.2 Defects in Photovoltaic Panels
2 Fault Identification System
2.1 Image Processing-Based Defect Identification
2.2 Machine Learning-Based Defect Identification
2.3 Deep Learning-Based Defect Identification
3 Experimental Results and Analysis
3.1 Canny Edge Detector
3.2 Support Vector Machine
3.3 AlexNet
4 Conclusion and Discussions
References
Covid Analysis Prediction Using Densenet Method in Deep Learning
1 Introduction
2 Related Work
3 Methodologies
3.1 DenseNet
4 Proposed Work
4.1 Need for Covıd Detectıon
4.2 Dataset
4.3 Server Creatıon
4.4 Identıfıcatıon of Covıd
4.5 System Architecture
5 Implementation and Results
6 Conclusion and Future Enhancement
References
Feature Extraction Based on GLCM and GLRM Methods on COVID-19 Dataset
1 Introduction
2 Literature Review
3 Proposed Methodology
3.1 Feature Extraction
3.2 Gray Level Co-Occurrence Matrixes
3.3 Gray Level Run Length Matrix
4 Classification Techniques
5 Results and Discussion
5.1 Performance Measures Parameters
6 Conclusion
References
Memory Augmented Distributed Monte Carlo Tree Search Algorithm-Based Content Popularity Aware Content Recommendation Using Content Centric Networks
1 Introduction
2 Related Works
3 MAD-MCTS-Based Content Recommendation System
3.1 System Model and Problem Formulation
3.2 Popularity Estimation
3.3 MAD-MCTS
4 Experiments and Results
4.1 Benchmark Dataset
4.2 Covid-19 Dataset
5 Conclusion
References
Enhancing Protection Against Scalper Bots with ML
1 Introduction
2 Existing System
2.1 Disadvantages
3 Proposed System
3.1 Block Diagram
3.2 Collecting User Timing Data
3.3 Training the Machine Learning Algorithm Using the Collected Data
3.4 Validating User
3.5 Improving the Accuracy of the Model
4 Implementation
4.1 Web Application
4.2 Checkout Bot
4.3 Bot Detection Model
5 Result
5.1 E-commerce Web Application
5.2 Detected a Human
5.3 Detected a Bot
5.4 Comparison Chart
6 Conclusion
References
An Enhanced Optimized Abstractive Text Summarization Traditional Approach Employing Multi-layered Attentional Stacked LSTM with the Attention RNN
1 Introduction
2 Associated Studies
3 Proffered Method
4 Preprocessing
4.1 Preprocessing Approaches
4.2 Noise Elimination
4.3 Sentence Dissection
4.4 Elimination of Punctuation Marks
4.5 Word Tokenization
4.6 Named Entity Recognition (NER)
4.7 Elimination of Stop Words
4.8 Stemming
5 Abstractive Text Summarization Paradigms
5.1 Classical LSTM Unit
5.2 Abstractive Summarization
5.3 MASta-LSTM-RNN Paradigm
6 Results and Discussion
7 Conclusion
References
Implementation of Machine Learning Methods on Data to Analyze Emotional Health
1 Introduction
2 Related Work
3 Experimental Analysis
4 Conclusion
References
Course Difficulty Estimation Based on Mapping of Bloom’s Taxonomy and ABET Criteria
1 Introduction
1.1 Bloom’s Taxonomy
1.2 ABET Criteria
1.3 Mapping ABET Criteria Students’ outcomes with Blooms’ Taxonomy
2 Literature Survey
3 Proposed Architecture
3.1 Course Difficulty Estimation
4 Results and Discussion
5 Conclusion
References