International Symposium on Intelligent Informatics: Proceedings of ISI 2022

Conference Organization
Preface
Contents
About the Editors
Artificial Intelligence and Machine Learning
DCLL—A Deep Network for Possible Real-Time Decoding of Imagined Words
	1 Introduction
	2 Dataset Used in the Study
	3 Data Augmentation
	4 Extracting the Features and LSTM Classifier
	5 Results
		5.1 Classification Accuracy
		5.2 Execution Time
	6 Conclusion
	References
Towards Frugal Artificial Intelligence: Exploring Neural Network Pruning and Binarization
	1 Introduction
	2 Related Concepts and Work
		2.1 Neural Network Pruning
		2.2 Neural Network Binarization
		2.3 Other Frugal AI-related Approaches
	3 Experimental Setup
	4 Experimental Results
		4.1 Baseline Performance Results
		4.2 Network Pruning Results
		4.3 Network Binarization Results
	5 Concluding Remarks
	References
Practical Implications of Dequantization on Machine Learning Algorithms: A Survey
	1 Introduction
	2 Quantum Machine Learning (QML)
		2.1 Quantum Memory
		2.2 Singular Value Transformation Using QRAM
	3 Quantum Inspired Classical Algorithms
		3.1 Sample and Query Access
		3.2 Quantum Inspired Machine Learning
	4 Practical Implementation Limitations
	References
Encoder–Decoder Network with Guided Transmission Map: Robustness and Applicability
	1 Introduction
	2 The EDN-GTM Scheme
	3 Data Preparation
		3.1 Atmospheric Scattering Model
		3.2 Synthesizing Hazy Data for Driving Object Detection
		3.3 Datasets
	4 Results on Benchmark Datasets and Applications to Driving Object Detection Tasks
		4.1 Dehazing Results on Realistic Haze Datasets
		4.2 Dehazing Results on Synthetic Hazy Dataset
		4.3 Object Detection Results on Synthetic Hazy Driving Scenes
		4.4 Object Detection Results on Natural Hazy Driving Scenes
	5 Conclusions
	References
Development of NN-Based Ball Bearing Fault Diagnosis Techniques
	1 Introduction
	2 Need for Machine Health Condition Monitoring
	3 Key Elements for Proposed Methodology
		3.1 Dataset
		3.2 Time-Domain Features
		3.3 Neural Network
		3.4 Fusion Techniques
	4 Results and Discussions
	5 Development of Graphical User Interface (GUI)
	6 Real-Time Simulation/analysis on Developed Model Using MATLAB SIMULINK
		6.1 Data Acquisition
		6.2 Feature Computation
		6.3 Neural Network Block
	7 Conclusion
	References
A Data Analytics-Based Study on Campaigns and Hashtags Movements Related to the Production of Fashion Goods
	1 Introduction
		1.1 Fashion Movements Related to Sustainability, Production, Factory Workers and Its Presence on Social Media
	2 Fashion Production Movements Related to Animals and Their Rights
		2.1 #anti-fur Movement
		2.2 #F.A.K. E
		2.3 #veganclothing
		2.4 Lettuce Ladies
	3 Greenwashing
		3.1 #h&mbrokepromises
		3.2 Zaful’s Manufacturing Chain
		3.3 Boohoo’s “Sustainable Collection”
	4 Results and Discussion
	5 Conclusion
	References
Gradual Search and Fixed Grouping Scheme Based Variant of Genetic Algorithm for Large Scale Global Optimization
	1 Introduction
	2 GA and Its Global Convergence Phenomena
		2.1 GA Misconvergence
	3 GA Variants for LSGO
		3.1 Novel Representation Types
		3.2 Various Search Schemes
		3.3 GA Variants or Various Search Strategies
	4 Performance Comparison on Standard Test Bench for LSGO
	5 Conclusion
	References
Generalized Symbolic Dynamics Weighted Network Prediction of Chaotic Time Series
	1 Introduction
	2 Methodology
	3 Results and Discussion
	4 Conclusions
	References
Automated Reduction of Detailed Biophysical Cerebellar Neurons to Izhikevich Neurons
	1 Introduction
	2 Methods
		2.1 Multicompartmental Biophysical Models
		2.2 Spiking Neuron Model
		2.3 Metaheuristic Algorithms
		2.4 Error Calculation
	3 Results
	4 Discussion
	5 Conclusion
	References
Comparative Study of Machine Learning and Deep Learning Classifiers on Handwritten Numeral Recognition
	1 Introduction
	2 Literature Survey
	3 Proposed Methodology
		3.1 Dataset
		3.2 Dataset Pre-processing
		3.3 Classification
	4 Experimental Setup and Discussion of Results
	5 Conclusion and Future Scope
	References
Segmentation Approach for Nucleus Cytoplasm of Ewing Sarcoma
	1 Introduction
		1.1 Objectives of the Study
	2 Material and Methods
		2.1 Data Set
		2.2 Pre-processing
		2.3 Image Segmentation
		2.4 Feature Extraction
		2.5 Classification
	3 Experiments
		3.1 Result Interpretation
	4 Discussion
	References
Deep Neuroevolution Squeezes More Out of Small Neural Networks and Small Training Sets: Sample Application to MRI Brain Sequence Classification
	1 Introduction
		1.1 Artificial Intelligence in Radiology Currently Focuses on Specific Tasks
		1.2 Early Promise, and Limitations, of Deep Reinforcement Learning
		1.3 Evolutionary Strategies: History, Background, and Major Strengths
		1.4 Radiology AI Currently Depends on Stochastic Gradient Descent
		1.5 Stochastic Gradient Descent Predisposes to Data Bias and Overfitting for Small Training Sets. Transfer Learning Helps but Shows Limitations
		1.6 Most Modern Radiology AI Uses Very Large (Deep) Neural Networks, but Small Networks Are Preferable for Clinical Deployment
		1.7 Prior Applications of Deep Neuroevolution to Radiology
		1.8 Application of Deep Neuroevolution to MRI Sequence Classification, and Prior Approaches to This Task
	2 Methods
		2.1 Data Collection
		2.2 Convolutional Neural Network (CNN)
		2.3 Classification Accuracy Provides the Fitness Criterion
		2.4 Deep Neuroevolution Selects for the Fittest Mutations and Passes Them on to Future Generations
		2.5 Deep Reinforcement Learning (DRL) Classification for Comparison
	3 Results
	4 Discussion/Conclusion
		4.1 Advantages of Deep Neuroevolution
		4.2 Drawbacks, Limitations, and Future Directions
	References
Natural Language Processing
Abstractive Text Summarization of Hindi Corpus Using Transformer Encoder-Decoder Model
	1 Introduction
	2 Related Works
		2.1 Findings of the Literature Review
	3 Methodology
		3.1 Data Pre-processing
		3.2 Transformer Model
	4 Experiments and Results
		4.1 Model Training
		4.2 Model Evaluation and Results
	5 Conclusions, Limitations and Future Work
	References
Automatic Text Classification for Web-Based Malayalam Documents
	1 Introduction
	2 Related Study
	3 Classification Problem and Models
		3.1 Classification Problem
		3.2 Classification Model
	4 Methodology
	5 Results and Discussions
	6 Conclusion
	References
Question and Answer Generation from Text Using Transformers
	1 Introduction
	2 Literature Review
	3 Methodology
		3.1 Dataset
		3.2 Fine-Tuning a T5 Transformer
	4 Implementation
		4.1 Data Preparation
		4.2 Tokenization
	5 Results and Analysis
	6 Conclusion
	References
A Comparative Study of Spam SMS Detection Techniques for English Content Using Supervised Machine Learning Algorithms
	1 Introduction
	2 Background Study
		2.1 Multinomial Naïve Bayes (MNB)
		2.2 Support Vector Machine (SVM)
	3 Related Work
	4 Methodology
		4.1 Dataset
		4.2 Dataset Splitting and Testing
		4.3 Data Preprocessing
		4.4 Data Training
	5 Evaluation Metrics
	6 Result
	7 Conclusion
	References
Evaluation of Tweet Sentiments Using NLP
	1 Introduction
	2 Blogging Sites and Machine Learning Techniques
		2.1 Opinion Mining
		2.2 Social Media
		2.3 Twitter
		2.4 Microblogging with E-commerce
		2.5 Twitter Sentiment Analysis
		2.6 Techniques of Sentiment Analysis
		2.7 Application Programming Interface
		2.8 Python
	3 Result Analysis
		3.1 Twitter Retrieved
		3.2 Sentiment Analysis
	4 General Observations
	5 Conclusion
	References
Signal, Image and Speech Processing
Cascaded Feature Vector Assisted Blood Vessel Segmentation from Retinal Images
	1 Introduction
	2 Literature Survey
	3 Proposed Method
		3.1 Feature Extraction
		3.2 Classification
	4 Experimental Analysis
		4.1 Datasets
		4.2 Performance Analysis
	5 Conclusion
	References
Unsupervised Deep Clustering and Reinforcement Learning Can Accurately Segment MRI Brain Tumors with Very Small Training Sets
	1 Introduction
	2 Methods
		2.1 Overview
		2.2 Data Collection
		2.3 Clustering
		2.4 Reinforcement Learning for Lesion Segmentation
	3 Results
		3.1 Application of Trained UDC and RL to Testing Set
		3.2 Training a U-net for Comparison
		3.3 Comparison Between Unsupervised Deep Clustering and Reinforcement Learning Segmentation Versus Supervised Deep Learning/U-net
	4 Discussion/Conclusion
	5 Conflicts of Interest
	References
EEG-Based Emotion Recognition Using an Ensemble Learning Algorithm
	1 Introduction
	2 Literature Review
	3 Emotion Model
	4 Proposed Work
		4.1 Dataset Description
		4.2 Method
	5 Results
	6 Conclusions
	References
Imaging and Vision Development Platform with Algorithm Library for Intelligent Vision Systems
	1 Introduction
	2 Architecture
	3 Implementation Strategy and Technology Integration
	4 Development and Deployment of Vision Application in the Intelligent Vision System Using the Imaging and Vision Development Platform
	5 Conclusions
	References
Pulse Decomposition Analysis Based Non-invasive Diabetes Detection System
	1 Overview
	2 Related Work
	3 Database
	4 Methodology
		4.1 Pre-processing
		4.2 Feature Extraction
		4.3 Classification
	5 Results
	6 Conclusion
	References
Noise Classification and Removal in Compressively Sensed Surveillance Videos Using Statistical Measures
	1 Introduction
	2 Noise Classification and Removal
	3 Compression and Reconstruction
		3.1 Compression of Video Frames Using CS
		3.2 Reconstruction Using NIPIRA
	4 Results and Discussions
		4.1 Performance of Noise Removal Algorithm for Various Variance Levels
		4.2 Performance Comparison with Existing Algorithms
	5 Conclusions
	References
DNA and Improved Sine Map Based Video Encryption
	1 Introduction
	2 Analysis of Theory Related
		2.1 Sine Map
		2.2 DNA Encoding and Its Rules
	3 Proposed Technique
		3.1 Encryption
		3.2 Decryption
	4 Results
		4.1 Experimental Setup
		4.2 Observations
	5 Conclusion and Future Work
	References
The Analysis of Srgb Color Space Based Density for Brain Tumor Segmentation
	1 Introduction
	2 Related Works
	3 Proposed Methodology
		3.1 Preprocessing Using Color Space and Gaussian Filter
		3.2 Possible Tumor Region Extraction
		3.3 Detection of Actual Tumor Region
		3.4 Post-processing for Eliminating Unwanted Regions
	4 Results
	5 Conclusion
	References
Improved Kapur Entropy-Based Lung Nodule Segmentation in X-ray Images
	1 Introduction
		1.1 Motivation
	2 Lung Nodule Segmentation
		2.1 Related Works
	3 Proposed Work
		3.1 Filtering
		3.2 Segmentation
	4 Results and Discussion
		4.1 Simulation Procedure
		4.2 Analysis of NIQE, PSNR, and SSIM
		4.3 Analysis Based on Filtering and Segmentation Techniques
	5 Conclusion
	References
Comparative Analysis of Various Standards for Medical Image Compression
	1 Introduction
	2 Literature Survey
	3 Brief Overview of Image/Video Compression Standards
		3.1 JPEG
		3.2 JPEG 2000
		3.3 AVC/H.264
		3.4 HEVC/H.265
	4 Methodology
	5 Results
	6 Conclusion
	References
Repetitive Filtering-Based Intra Prediction Scheme for HEVC
	1 Introduction
	2 Comparative Analysis of Coding Gain
		2.1 Coding Gain Variation with the Sample Value N of Pixel
		2.2 Coding Gain Variation with Deviation of Sample Pixel
	3 Proposed Repetitive Filtering Intra Prediction Optimized Through Rate Distortion
		3.1 Intra Prediction with Repetitive Filtering
	4 Experimental Results
	5 Conclusion
	References
Identification and Counting of Blood Cells Using Machine Learning and Image Processing
	1 Introduction
	2 Literature Review
	3 Methodology
	4 Result
	5 Conclusion
	References
EDGE-Based ML in W-Band Target Micro-Doppler Feature Extraction
	1 Introduction
	2 System Design
	3 Results and Discussion
	4 Conclusions
	References
Emotion Detection Using Speech Analysis
	1 Introduction
	2 Literature Review
	3 Proposed Work
		3.1 Dataset
		3.2 Feature Extraction
		3.3 Block Diagram
	4 Result and Analysis
	5 Conclusion and Future Scope
	References
Communication Networks and Distributed Systems
FED6G: Chameleon Learning for Network Slice Management in Beyond 5G Systems
	1 Introduction
	2 Network Slicing and Machine Learning in B5G
	3 Related Work
	4 FED6G Model Overview
	5 FED6G Model Evaluation
	6 Conclusion
	References
H-SWIPT Based Energy-Efficient Clustering for Multi-Hop IoT Networks
	1 Introduction
	2 Literature Review
	3 Proposed Method
		3.1 Overview
		3.2 Energy Model
		3.3 Clustering
	4 Simulation Results
		4.1 Simulation Setup
		4.2 Performance Analysis
	5 Conclusion
	References
Application Mapping onto Network on Chip Using Cat Swarm Optimization
	1 Introduction
	2 Related Work
	3 Application Mapping Problem
		3.1 Noc Model
		3.2 Objective Function
	4 CAT Swarm Optimization
	5 Experiment Result
		5.1 Setting
		5.2 Result and Discussion
	6 Conclusion
	References
Advances in Vision-Based UAV Manoeuvring Techniques
	1 Introduction
	2 Approaches for Vision-Based Manoeuvring
		2.1 Autonomous UAV Navigation in Indoor Corridor Environments Using Convolutional Neural Network
		2.2 Outdoor UAV Navigation Using Optical Flow and DEM Matching
		2.3 UAV Navigation Using Image Processing―Position Enhancement
		2.4 Position Estimation of a UAV Using Particle Filter
		2.5 Camera Based Horizontal and Vertical Drone Landing System
		2.6 Autonomous Flight Control Using vSLAM Algorithm
		2.7 UAV Landing Based on the Optical Flow Video Navigation
		2.8 UAV Guidance for Autonomous Landing Using Deep Neural Networks Such as CNNs
		2.9 Deep Learning Techniques for Autonomous Drone Navigation
		2.10 Autonomous Lunar Landing Using GPOPS
	3 Conclusion
	References
Modeling the Impact of Fake Data Dissemination During Covid-19
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 SIR Epidemiological Model
		3.2 Fake Data and Trust
	4 Results and Analysis
		4.1 Net Logo Simulation Setup
		4.2 SIR Fake Data Simulation
		4.3 Analysis of Trust
	5 Conclusion
	References
On Ups and Downs in Analyzing Web Activity Data: Notes from a Project
	1 The Context and Its Conditioning
		1.1 The Overwhelming Web
		1.2 The Misuses and Threats, but also Opportunities
		1.3 The Routine Analytical and Design Procedure
	2 The Web-Based Advertising Market
	3 The Artificial Activity and Its Main Characteristics
	4 Feature Analysis—Essential Glimpses
		4.1 Some Temporal Characteristics
		4.2 Correlation Analysis
		4.3 Principal Component Analysis
	5 Clustering
	6 Hybrid Classifiers
	7 Conclusions
	References
Author Index