Machine Intelligence Techniques for Data Analysis and Signal Processing: Proceedings of the 4th International Conference MISP 2022, Volume 1

✍ Scribed by Dilip Singh Sisodia; Lalit Garg; Ram Bilas Pachori; M. Tanveer

• Publisher: Springer Nature
• Year: 2023
• Tongue: English
• Leaves: 879
• Category: Library

✦ Synopsis

This book comprises the proceedings of the 4th International Conference on Machine Intelligence and Signal Processing (MISP2022). The contents of this book focus on research advancements in machine intelligence, signal processing, and applications. The book covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. It also includes the progress in signal processing to process the normal and abnormal categories of real-world signals such as signals generated from IoT devices, smart systems, speech, and videos and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG), electromyogram (EMG), etc. This book proves a valuable resource for those in academia and industry.

✦ Table of Contents

About the Editors
Contents
On Diverse and Serendipitous Item Recommendation: A Reinforced Similarity and Multi-objective Optimization-Based Composite Recommendation Framework
1 Introduction
2 Related Work
2.1 End-User Personalized Traditional Recommendation System
2.2 Multi-Objective Recommendation Model
2.3 Motivation
3 Proposed Multi-stakeholder Recommendation Model
3.1 The Proposed Multi-objective Recommendation Framework (MORF)
3.2 Reinforced Similarity-Based Rating Prediction
3.3 Objective Functions
3.4 Evaluation Metrics
4 Experiments
4.1 Experimental Data
4.2 Competing Algorithm
4.3 Experimental Results Analysis and Discussion
5 Conclusion
References
Comparative Analysis of Node-Dependent and Node-Independent Graph Matrices for Brain Connectivity Network
1 Introduction
2 Methodology
2.1 Dataset
2.2 Brain Connectivity Network
2.3 Distance and Similarity Measures Calculation
3 Results
4 Conclusion and Future Scope
References
Facial Expression Recognition from Low Resolution Facial Segments Using Pre-trained Networks
1 Introduction
2 Related Work
3 Database and Pre-processing
3.1 Reduction in Spatial Resolution
4 Proposed Methodology
4.1 Spatial Exploitation-Based CNN (SEB-CNN)
4.2 Depth-Based CNN (DB-CNN)
4.3 Channel Exploitation-Based CNN (CEB-CNN)
5 Results
5.1 Results of SEB-CNN, DB-CNN and CEB-CNN on Full Face Low Resolution Images
5.2 Results of SEB-CNN, DB-CNN and CEB-CNN on Half Face Low Resolution Images
5.3 Results of SEB-CNN, DB-CNN and CEB-CNN on Quarter Face Low Resolution Images
6 Conclusion and Future Scope
References
Design and Analysis of Quad Element UWB MIMO Antenna with Mutual Coupling Reduction Techniques
1 Introduction
2 Antenna Design
3 Mimo System Design
3.1 Double-Sided MIMO Antenna
3.2 Decoupling Structure Technique
3.3 Neutralization Line Technique
3.4 Ground Plane Stub
4 Results Ad Discussion
5 Conclusion
References
Enhancing Agricultural Outcome with Multiple Crop Recommendations Using Sequential Forward Feature Selection
1 Introduction
2 Literature Review
3 Methodology
3.1 Dimensionality Reduction
3.2 Feature Subset Identification
3.3 Crop Prediction
4 Experimental Results and Discussion
5 Multi Crop Recommendation
6 Comparison
7 Conclusion and Future Enhancement
References
Kernel-Level Pruning for CNN
1 Introduction
2 Related Work
3 Methodology
4 Result and Analysis
5 Conclusion and Future Work
References
Linear Regression Model for Predicting Virtual Machine Consolidation Within the Cloud Data Centers (LrmP_VMC)
1 Introduction
2 Related Work
3 Design and Implementation
3.1 Overall Design
3.2 Architecture Diagram
3.3 Power Model
3.4 Evaluation and Selection
3.5 The Overall Proposed Algorithm
4 Simulation and Experimental Results
4.1 Experimental Setup
4.2 Evaluation Metrics
4.3 Performance Evaluation
4.4 Comparing the Genetic Algorithm with Other Methods
5 Conclusion and Future Scope
References
Detection of Fraudulent Credit Card Transactions Using Advanced LightGBM Approach
1 Introduction
2 Related Works
3 Proposed Approach
3.1 Data Preprocessing
3.2 Feature Selection
3.3 Performing Advanced LightGBM
3.4 Evaluation Metrics
4 Experimental Results
5 Conclusion
References
Approach of Different Classification Algorithms to Compare in N-gram Feature Between Bangla Good and Bad Text Discourses   
1 Introduction
2 Literature Review
3 Methodology
3.1 Dataset Description
3.2 Data Preprocessing
3.3 Data Encoding
3.4 Model Implementation
3.5 Performance Calculation
4 Results and Discussions
5 Conclusion
References
Effective Heart Disease Prediction Using Hybrid Ensemble Learning Model
1 Introduction
2 Data Description
3 Proposed Model
3.1 Hybrid Ensemble Model
4 Experimental Results
4.1 Data Preprocessing Results
4.2 Data Analysis Results
4.3 Performance Evaluation
5 Conclusion
References
A SAR ATR Using a New Convolutional Neural Network Framework
1 Introduction
2 Proposed Methodology
2.1 Dataset Used
2.2 Data Preprocessing
2.3 Proposed Convolutional Neural Network
3 Result and Discussion
4 Conclusion and Future Scope
References
A Distributed Data Fusion Approach to Mitigate Node Redundancies in an IoT Network
1 Introduction
1.1 Motivation
1.2 Literature Review
1.3 Contributions and Paper Organization
2 Threshold-Based Pearson’s Divergence to Identify the Redundancies
3 Proposed Model
4 Results and Comparative Analysis
5 Conclusion
References
ColCompNeT: Deep Learning-Based Colorization-Based Coding Network
1 Introduction
2 Methodology
3 Implementation Details
3.1 Dataset
3.2 Hyperparameter Tuning
3.3 Evaluation Parameters
4 Results and Discussion
5 Conclusion and Future Scope
References
Printed Elliptical Cut Vivaldi 1 × 5 Linear Array Antenna for X and KU Band Applications
1 Introduction
2 Single Antenna Geometry
3 Vivaldi 1 × 5 Linear Array Antenna Analysis
3.1 Rectangular and Circular Cavity
4 Simulation Results
4.1 Voltage Standing Wave Ratio (VSWR)
4.2 Gain
4.3 Radiation Patterns
5 Experimental Results
5.1 Measured Return Loss
5.2 Gain Plot
6 Conclusion
References
Texture Classification Using ResNet and EfficientNet
1 Introduction
2 Literature Review
3 Materials and Methods
3.1 Data set
3.2 Data Pre-processing and Splitting
3.3 Data Augmentation
3.4 Deep Learning Models
4 Experiments and Results
4.1 Evaluation Criteria
4.2 Training Single Convolution Model
4.3 Comparative Study
5 Conclusion and Future Scope
References
Performance Analysis of Parametric and Non-parametric Classifier Models for Predicting the Liver Disease
1 Introduction
2 Related Work
3 Methodology
3.1 Dataset
3.2 Machine Learning Algorithms
3.3 Classifier Performance Evaluation
4 Experimental Results and Discussion
5 Conclusion
References
angularParameter: A Novel Optimization Technique for Deep Learning Models
1 Introduction
2 Related Work
3 The Proposed Optimizer
4 Empirical Analysis
5 Experimental Results and Discussion
5.1 Convergence Analysis Using Rosenbrock Function
5.2 Image Classification Results on CIFAR10 and CIFAR100 Data sets
6 Conclusion
References
Efficient Prediction of Annual Yield from Stocks Using Hybrid Deep Learning
1 Introduction
2 Related Work
3 Data and Background
3.1 Problem Formulation
3.2 Background
3.3 Data
4 Method
4.1 LSTM Network
4.2 Hybrid CNN-LSTM Model
5 Performance and Evaluations
5.1 Training Performance
5.2 Evaluations
6 Conclusion and Future Work
References
Multitask Deep Learning Model for Diagnosis and Prognosis of the COVID-19 Using Threshold-Based Segmentation with U-NET and SegNet Classifiers
1 Introduction
2 Related Works
3 Methodology and Analysis
3.1 Region-Based Segmentation
3.2 Threshold Segmentation
3.3 Region Growing in Proposed System
3.4 Active Contour Models
4 Results and Discussions
4.1 Binary Classification Issues
5 Conclusion
References
Deep Neural Transfer Network Technique for Lung Cancer Detection
1 Introduction
2 Related Works
3 Methodology and Methods
3.1 Training and Testing Data Splitting
4 Results and Discussions
5 Conclusions
References
Criminal Tendency Identification Using Deep Learning Approaches: A Novel Approach for Security Protection
1 Introduction
2 Related Works
3 Proposed Method
4 Materials and Methods
4.1 Dataset Description
5 Results and Discussions
6 Conclusions and Future Scope
References
Banana Ripeness Identification and Classification Using Hybrid Models with RESNET-50, VGG-16 and Machine Learning Techniques
1 Introduction
2 Dataset Description
3 Literature Survey
4 Techniques Employed
4.1 VGG-16
4.2 ResNet-50
4.3 Naïve Bayes
4.4 K-Nearest Neighbour
4.5 Support Vector Machine
4.6 Logistic Regression
5 Results
5.1 Accuracy
5.2 R-Squared
5.3 Mean Squared Error
5.4 Mean Absolute Error
5.5 Precision
5.6 Comparative Results
5.7 Predictions
6 Compliance with Ethical Standards
7 Conclusion
References
The Study of Effectiveness of Automated Essay Scoring in MOOCs
1 Introduction
2 Related Works
3 Integrating Automated Essay Scoring into MOOC Platforms
3.1 Proposed Evaluation System’s Components
4 Methods: Automated Essay Scoring
4.1 Dataset
4.2 The Processing of the Essays
5 Results and Discussion
5.1 Single Feature Kappa
5.2 Greedy Forward Selection
5.3 Optimization: Word2vec Model
6 Conclusion
References
Remote Authentication of IoT Devices Based Upon Fog Computing
1 Introduction
2 Proposed System Model
2.1 Initialization Phase
2.2 Authentication Phase
2.3 Communication Phase
3 Experiment and Result Discussion
3.1 Time and Power Consumption
3.2 Security Analysis
3.3 Performance Evaluation
4 Conclusion
References
Comparison of Different Denoising Networks on Motion Artifacted MRI Scans
1 Introduction
2 Literature Review
3 Methodology
3.1 Dataset
3.2 Modified Restricted Boltazmann Machine (mRBM)
3.3 Conditional Generative Adversarial Network (cGAN)
3.4 Denoising Convolutional Neural Network (DnCNN)
4 Results and Discussions
4.1 Root Mean Square Error (RMSE)
4.2 Peak Signal-to-Noise Ratio (PSNR)
4.3 Mutual Information (MI)
4.4 Structural Similarity Index Measure (SSIM)
4.5 Pixel Deviation
4.6 Best Performing Model for MRI Scans of Various Parts of the Body
5 Conclusion
References
Plant Species Recognition Using Custom-Developed Neural Network with Optimized Hyperparameters
1 Introduction
2 Related Works
3 Methodology
4 Results and Discussion
4.1 Determination of Activation Function
4.2 Determination of Optimizer
4.3 Determination of Learning Rate
4.4 Determination of Epoch
5 Conclusion
References
Implementation of Legal Documents Text Summarization and Classification by Applying Neural Network Techniques
1 Introduction
2 Related Works
3 Dataset
4 Experiments
4.1 BERT Model
4.2 RoBERTa Model
4.3 XLNet Model
5 Results Analysis
5.1 Comparison of Different Models
5.2 Error Analysis
6 Conclusion
References
Robust Image Watermarking Using Arnold Map and Adaptive Threshold Value in LWT Domain
1 Introduction
1.1 Important Contribution
2 Preliminaries
2.1 Lifting Wavelet Transform (LWT)
2.2 Arnold Cat Map (ACM)
3 Proposed Method
3.1 Block Identification Method (BIM)
3.2 Watermark Adding Procedure
3.3 The Decoder Design
3.4 Watermark Extraction Method
4 Results and Discussion
5 Conclusion and Future Scope
References
Handcrafted and Deep Features for Micro-expressions: A Study
1 Introduction
2 Micro-expression: Duration and Database
3 Stages of Micro-expression Detection and Identification
3.1 Preprocessing
3.2 Feature Extraction
3.3 Classification
4 Issues and Implications
5 Conclusion and Future Scope
References
Multiclass Text Emotion Recognition in Social Media Data
1 Introduction
1.1 Objectives
1.2 Emotion Recognition
1.3 Natural Language Processing
1.4 Social Media Analytics
2 Related Work
3 Proposed System
3.1 Architecture
3.2 Module Description
4 Experimental Results
5 Summary and Conclusions
6 Compliances with Ethical Standards
References
Machine Learning-Based Technique for Phishing URLs Detection from TLS 1.2 and TLS 1.3 Traffic Without Decryption
1 Introduction
2 Literature Survey
2.1 Content-Based Methods for Phishing Detection
2.2 List-Based Methods for Phishing Detection
2.3 URL Feature-Based Methods for Phishing Detection
3 Proposed Work
4 Experimentation and Results
4.1 Dataset
5 Conclusion
References
Robust Pipeline for Detection of Adversarial Images
1 Introduction
2 Related Work
3 Background Work
3.1 Fast Gradient Signed Method (FGSM) Attack
3.2 Patch Attack
3.3 Projected Gradient Descent (PGD) Attack
3.4 Mantra-Net
4 Methodology
4.1 ILSVRC 2012 Dataset
4.2 Workflow
4.3 Creation of Adversarial Image Dataset
4.4 Extraction of Manipulation Masks
4.5 Training a Binary Classifier
5 Results and Discussion
6 Conclusion and Future Work
References
A Hybrid Approach Using Wavelet and 2D Convolutional Neural Network for Hyperspectral Image Classification
1 Introduction
2 Literature Survey
3 Proposed Methodology
3.1 Dataset Description
3.2 Description of the Model
4 Experimental Result and Discussion
4.1 Performance Measurement Criteria
4.2 Experimental Results
5 Conclusion
References
Assessment of Visual Stress Using EEG Signals
1 Introduction
2 Methodology
2.1 Data Set
2.2 Feature Extraction
3 Hypothesis Testing
4 Classification
5 Results and Discussions
6 Conclusion
References
A Novel Recommendation System for Vaccines Using Hybrid Machine Learning Model
1 Introduction
2 Related Work
3 Proposed System
3.1 Dataset Collection
3.2 Data Preprocessing and Analytics
3.3 Recommendation Methodology
4 Performance Evaluation
5 Conclusions and Future Work
References
SiamLBP: Exploiting Texture Discrepancies for Deepfake Detection
1 Introduction
2 Related Work
3 Proposed Methodology
3.1 LBP-Based Feature Extraction
3.2 Siamese Training for Texture Feature Comparison
3.3 Datasets
4 Implementation and Performance Evaluation
4.1 Hyperparameters
4.2 Evaluation Results
5 Conclusion
References
Rainfall Prediction Using Machine Learning
1 Introduction
2 Literature Review
3 Rainfall Prediction Using Machine Learning Technique
3.1 Dataset Description
3.2 Rainfall Prediction Using Machine Learning Technique
3.3 Performance Evaluation
3.4 Description of Evaluation Metrics
4 Experimental Results
5 Conclusion
References
Explainable AI Model to Minimize AI Risk and Maximize Trust in Malignancy Detection of the Pulmonary Nodules
1 Introduction
2 Background
3 Proposed Model with Methodology
4 Implementation and Results Discussions
4.1 Machine Learning Model
4.2 Explainable AI
5 Conclusion with Future Work
References
Empirical Analysis of Hybrid Classical Variational Quantum Neural Networks for Target Classification from SAR Data
1 Introduction
2 Hybrid Classical-Quantum Circuits
2.1 Encoders
3 Dataset
4 Results and Discussion
5 Conclusion and Future Work
References
COVID-19 Social Distancing Detection and Email Violation Mechanisms
1 Introduction
2 Literature Survey
3 Methodology
3.1 Object Detection in Video
3.2 People Class Detection
3.3 Camera Perspective Transformation
3.4 Distance Estimation Between Pedestrians
3.5 Bounding Box Generation
3.6 Email Alert Mechanism
4 Experimental Analysis
5 Conclusion
References
Evaluating Generative Adversarial Networks for Gurumukhi Handwritten Character Recognition (CR)
1 Introduction
2 Related Work
3 Types of GAN Architecture for Gurumukhi Handwritten CR
3.1 Deep Convolution GAN (DCGAN)
3.2 Wasserstein GAN (WGAN)
3.3 Least Square GAN (LSGAN)
3.4 Conditional GAN
4 Experiments and Results
5 Conclusion and Future Scope
References
Evaluating Feature Importance to Investigate Publishers Conduct for Detecting Click Fraud
1 Introduction
2 Methods and Materials
2.1 Block Diagram
2.2 Data Acquisition
2.3 Feature Extraction
2.4 Evaluating Feature Importance Scores
2.5 Classification Algorithms
2.6 Cross-validation and Evaluation Measures
3 Experimental Results
4 Conclusion
References
A Deep Learning Model Based on CNN Using Keras and TensorFlow to Determine Real-Time Melting Point of Chemical Substances
1 Introduction
2 Fundamental Theory
2.1 CNN
2.2 TensorFlow and Keras
2.3 ReLu and Sigmoid
2.4 Dataset
2.5 Problem Formation
3 Related Research
4 Proposed Deep Learning Model
5 Proposed DL Model Implementation
6 Results
7 Conclusion
References
EEG Emotion Recognition Using Convolution Neural Network
1 Introduction
2 Related Work
3 Method
3.1 Feature Extraction
3.2 Convolutional Neural Network
3.3 Implementation Details
4 Experiment
4.1 SEED IV Dataset and Preprocessing
4.2 Train CNN
5 Result and Discussion
6 Conclusion
References
CCL-Net: Complete Comprehensive Learning and Modality Preserving-Based RGBD Complex Salient Object Detection
1 Introduction
2 Related Works
3 The Proposed Method
3.1 Multi-scale Non-complementary Features Aggregation
3.2 Complete Comprehensive Learning Model
3.3 Saliency Qualifier Fusion Model-SQF
3.4 Loss Function
4 Experiment Set-Up and Result Analysis
4.1 Dataset and Evaluation Metrics
4.2 Implementation Details
4.3 Comparison and Result Analysis
4.4 Validation of Three-Stream Networks
5 Conclusion
References
LexRank and PEGASUS Transformer for Summarization of Legal Documents
1 Introduction
2 Related Work
2.1 Summarization for Legal Documents
2.2 Domain Independent Summarization Techniques
3 Paraphrasing Using Natural Language Processing (NLP)
4 Proposed Method
4.1 LexRank Summarization Algorithm
4.2 PEGASUS Transformer
4.3 Implementation
5 Results
5.1 ROUGE Scores
5.2 Sample Output
6 Conclusion and Future Scope
References
DoS Defense Using Modified Naive Bayes
1 Introduction
2 Related Work
3 Proposed Solution
3.1 Fingerprint Gathering
3.2 Intrusion Detection System
4 Attack Analysis
4.1 Attack Statistics
4.2 DOS Attacks
5 Conclusion
References
Adaptive Threshold Peak Detection for Launch Vehicle Simulation Time Series Data Analysis
1 Introduction
2 Data Characteristics
3 Implementation of Peak Detection Strategy
4 Algorithms for Data Transformation
5 Piecewise Approach for Adaptive Threshold Generation
5.1 Divided Average Method (DAM)
5.2 Moving Average Method (MAM)
6 Parameters for Performance Evaluation
7 Results and Discussion
8 Performance Analysis Using Contingency Matrix
9 Conclusion
References
Clustering for Global and Local Outliers
1 Introduction
2 Related Work
3 Problem Formulation
3.1 Hierarchical Clustering
3.2 Isolation Forest
3.3 Algorithm
4 Experiments
4.1 Dataset
4.2 Experimental Setup
5 Results and Analysis
5.1 Discussion
6 Conclusion
References
Smart Timer Module for Handheld Demolition Tools
1 Introduction
1.1 Working of Demolition Hammers
1.2 Objective
1.3 Methodology
2 Literature Survey
2.1 Early Developments in Demolition Hammer
2.2 Electronic Design Reference
3 Implementation
3.1 Timer Configuration and Operation
3.2 MPU6050 Configuration and Operation
3.3 User Interface
3.4 EEPROM Operations
3.5 Circuits and PCB
4 Hardware and Software Tools Used
5 Result
5.1 Boot Up
5.2 Selection
5.3 Time Recording
5.4 Previous Values
5.5 Error Analysis
6 Conclusion
References
Dynamic Hand Gesture Recognition Using mYOLO-CSRT and HGCNN for Human–Machine Interaction
1 Introduction
2 Proposed Methodology
2.1 Dataset Collection and Labeling
2.2 Preparation of Configuration File
2.3 Labeled Dataset Training and Hand Detection
2.4 Hand Tracking and Gesture Formation
2.5 Gesture Classification
3 Result Analysis
4 Hardware Application
5 Conclusion
References
Cov-CONNET: A Deep CNN Model for COVID-19 Detection
1 Introduction
2 Literature Review
2.1 Machine Learning-Based Approaches
2.2 Deep Learning and Pre-trained Model-Based Approaches
3 Methodology
3.1 Data Set
3.2 Algorithms Used
4 Results and Analysis
4.1 Experimental Analysis and Results
4.2 Validation Results and Comparative Analysis with Existing Work
5 Conclusion
References
AI-Based Real Time Object Measurement Using YOLO V5 Algorithm
1 Introduction
2 Literature Survey
3 Flow Diagram
4 Methodology
4.1 Algorithm—Open CV and Yolo V5
5 Result and Discussion
6 Conclusion
References
Prediction of Heart Abnormality Using Heart Sound Signals
1 Introduction
2 Related Work
3 Proposed Work
4 Methodology
4.1 Logistic Regression Hidden Semi Markov Model
4.2 Bonferroni Mean-Based Fuzzy K-Nearest Centroid Neighbor Classifier (BM-FKNCN)
5 Implementation
5.1 Preprocessing and Segmentation
5.2 Feature Extraction
5.3 Classification
6 Result
7 Conclusion
References
An Intelligent Smart Waste Management System Using Mobile Application and IoT
1 Introduction
2 Literature Review
3 Proposed Methodology
3.1 Microcontroller for Interfacing the Sensors
3.2 Sensor for Measurement of Waste Level in Dustbin
3.3 Sensor for Detecting Animals
3.4 Sensor for Communication
3.5 Mobile Application
3.6 Server
4 Results and Discussion
4.1 Screenshots
4.2 Prototype
4.3 Usability Testing
5 Conclusion
References
Pan-Sharpening of Multi-spectral Remote Sensing Data Using Multi-resolution Analysis
1 Introduction
2 Materials and Methods
2.1 Study Area and Dataset
2.2 Experimental Setup and Pre-processing
2.3 Discrete Wavelet Transform (DWT)
2.4 Steps for Fusion
3 Results and Discussion
4 Conclusion
References
Detection of Malaria by Using a CNN Model
1 Introduction
2 Motivation
3 Related Work
4 Proposed Methodology
4.1 Stage 1: Dataset Summarization
4.2 Stage 2: Convolutional Neural Network
5 Experimental Results and Discussion
6 Conclusion and Future Works
References
Session-Based Song Recommendation Using Recurrent Neural Network
1 Introduction
2 Related Work
3 Proposed Method
4 Result and Discussion
4.1 Dataset Description
4.2 Dataset Splitting Approach
4.3 Evaluation Metrics
4.4 Comparative Result
5 Conclusion and Future Work
References
The Classification of Breast Cancer Based on Hyper-Tuned AdaBoost Ensemble Model
1 Introduction
2 Literature Review
3 Proposed Approach
3.1 Dataset Description
3.2 Data Preprocessing
3.3 Data Visualization
3.4 Tuned AdaBoost Ensemble Model
4 Results and Evaluation
5 Conclusion
References
Detection of COVID-19-Affected Persons Using Convolutional Neural Network from X-Rays’ Images
1 Introduction
1.1 Overview
2 Literature Survey
3 Methodology
3.1 Dataset
3.2 Method
3.3 Evaluation of Performances of Proposed Model
4 Results
5 Discussion
6 Conclusion
References
Vehicle Theft Identification Using Machine Learning and OCR
1 Introduction
2 Related Work
3 Methodology
4 Experiment Details
4.1 Experimental Evaluation
4.2 Results and Discussion
4.3 Comparative Analysis
5 Conclusion and Future Scope
References
Ransomware Attack Detection by Applying Machine Learning Techniques
1 Introduction
1.1 Motivation
2 Literature Review
3 Methodology
3.1 Dataset
3.2 Preprocessing
3.3 Feature Selection
3.4 Synthetic Minority Oversampling Technique
3.5 Model Training
4 Experimental Results
4.1 Without Any Feature Selection Techniques
4.2 Chi-Square Test
4.3 Pearson’s Correlation Coefficient
4.4 Forward Selection
4.5 Backward Elimination
4.6 Lasso Regularization (L1)
5 Conclusion
References
Weed Detection in Soybean Crop Using YOLO Algorithm
1 Introduction
2 Related Works
3 Methodology
3.1 Data Collection and Labeling
3.2 System Setup
3.3 You Only Look Once Algorithm for Weed Detection
3.4 Performance Metrics
4 Results and Discussions
4.1 Quantitative Results
4.2 Qualitative Results
5 Conclusion
References
An IoT Machine Learning Model-Based Real-Time Diagnostic and Monitoring System
1 Introduction
2 Related Work
3 The Machine Learning-Enabled Internet of Medical Things (IoMT)-Based Disease Diagnosis Model
3.1 Case Study
3.2 The Machine Learning Algorithms
4 Performance Evaluation Metrics
5 Results and Discussion of the Findings
5.1 The Proposed Classifier’s Performance
5.2 Confusion Matrix
6 Conclusion and Directions for Future Work
References
Hausa Character Recognition Using Logistic Regression
1 Introduction
2 Materials and Methodology
3 Results and Discussion
4 Results and Discussion
5 Conclusion
References
Long Short-Term Memory-Driven Recurrent Neural Network for Real-Time Stock Monitoring and Prediction
1 Introduction
2 Literature Review
3 Architecture of LSTM
3.1 Overview of Recurrent Neural Networks (RNN)
3.2 LSTM Networks
4 Material and Methods
5 Result and Discussion
6 Conclusion and Future Work
References
Performance Evaluation of TQWT and EMD for Automated Major Depressive Disorder Detection Using EEG Signals
1 Introduction
2 Methods and Materials
2.1 Data Acquisition
2.2 Decomposing EEG Signal Using TQWT and EMD Methods
2.3 Feature Extraction
2.4 Feature Significant Test
2.5 Classifiers
3 Results and Discussions
3.1 Results
3.2 Discussions
4 Conclusion
References
Smart Crop Recommendation System: A Machine Learning Approach for Precision Agriculture
1 Introduction
1.1 Objective
1.2 Research Contribution
2 Literature Review
3 Implementation
3.1 Dataset Description
3.2 ML Models Used
3.3 Evaluation Parameters
4 Results
5 Research Opportunities and Challenges
6 Conclusion
References
Digital Image Transformation Using Outer Totality Cellular Automata
1 Introduction
2 Threshold Frequency
3 Luminosity Method
4 Vitality Function
5 Experimental Results
6 Conclusion and Future Scope
References
Community Detection Using Context-Aware Deep Learning Model
1 Introduction
2 Literature Review
3 Deep Learning Model Architecture
4 Data Set and Experimental Setup
5 Experimental Results
6 Conclusion and Future Scope
References
Discriminative Feature Construction Using Multi-labeling Approach for Automatic Speech Emotion Recognition
1 Introduction
2 Proposed Framework
2.1 Emotion Classification as a Multi-label Classification Problem
2.2 Discriminative Feature Construction
2.3 Speech Emotion Recognition Using Multi-label Features
3 Result and Discussion
3.1 Performance Analysis: Single-Label and Multi-label Models
3.2 Comparison with State-of-the-Art Results
4 Conclusion
References
Intuitionistic Fuzzy Kernel Random Vector Functional Link Classifier
1 Introduction
2 Related Models
2.1 Random Vector Functional Link Network (RVFL)
2.2 Intuitionistic Fuzzy Number
3 Intuitionistic Fuzzy Kernel Random Vector Functional Link Network (IFK-RVFL)
4 Numerical Experiments
4.1 Simulation on a Few Real-World Datasets
5 Conclusion and Future Direction
References
Mapping of Waterlogged Areas and Silt-Affected Areas After the Flood Using the Random Forest Classifier on the Sentinel-2 Dataset
1 Introduction
2 Literature Review
3 Study Area
4 Dataset Preparation and Preprocessing
4.1 Sentinel-2 Data
4.2 Image Preprocessing
5 The Methodology and Classifiers Used
5.1 Methodology
5.2 Classifiers Used
6 Results and Discussion
7 Conclusion
References