Advances and Applications of Artificial Intelligence & Machine Learning: Proceedings of ICAAAIML 2022 (Lecture Notes in Electrical Engineering, 1078)

✍ Scribed by Bhuvan Unhelkar (editor), Hari Mohan Pandey (editor), Arun Prakash Agrawal (editor), Ankur Choudhary (editor)

• Publisher: Springer
• Year: 2023
• Tongue: English
• Leaves: 782
• Edition: 1st ed. 2023
• Category: Library

✦ Synopsis

This volume comprises the select peer-reviewed proceedings of the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning 2022 (ICAAAIML 2022). It aims to provide a comprehensive and broad-spectrum picture of state-of-the-art research and development in the areas of artificial intelligence, machine learning, deep learning, and their advanced applications in computer vision and blockchain. It also covers research in core concepts of computers, intelligent system design and deployment, real-time systems, WSN, sensors and sensor nodes, software engineering, image processing, and cloud computing. This volume will provide a valuable resource for those in academia and industry.

✦ Table of Contents

Contents
About the Editors
Development of Big Data Dimensionality Reduction Methods for Effective Data Transmission and Feature Enhancement Algorithms
1 Introduction
2 Works
3 Objectives
4 Proposed Dimensionality Reduction Method
5 Analysis of the Obtained Results
6 Conclusion
References
IndianFood-7: Detecting Indian Food Items Using Deep Learning-Based Computer Vision
1 Introduction
2 Literature Review
3 Methodology
3.1 Data Preparation
3.2 Our Experimentation on Object Detection Models
4 Results
5 Conclusion
References
Prediction of Protein-Protein Interaction Using Support Vector Machine Based on Spatial Distribution of Amino Acids
1 Introduction
2 Experimental Setup
3 Methodology
3.1 Data Set
3.2 Feature Representation
3.3 Support Vector Machines (SVM)
4 Results and Discussion
4.1 Evaluation Metrics
4.2 Performance of Proposed Model
4.3 Proposed Model Comparison Against Various Predictors
5 Conclusion
References
A Computational Comparison of VGG16 and XceptionNet for Mango Plant Disease Recognition
1 Introduction
2 Methodology and Dataset
2.1 Architecture of the Proposed System
2.2 Dataset Description
2.3 Data Pre-processing
2.4 Models Used
2.5 Training and Compiling the Model
3 Result and Analysis
4 Conclusion
References
Generate Artificial Human Faces with Deep Convolutional Generative Adversarial Network (DCGAN) Machine Learning Model
1 Introduction
2 Related Work
3 Methodology
3.1 Experimental Setup
3.2 Dataset Description
3.3 Model Description
4 Results
5 Future Scope and Conclusion
References
Robust Approach for Person Identification Using Three-Triangle Concept
1 Introduction
2 Literature Review
3 Methodology
3.1 Block Diagram of Recommended System
3.2 Algorithm Used
4 Circuit Layout
5 Interfacing of Components
6 Experimental Results
7 Conclusions
8 Future Scope
References
COVID-19 Disease Detection Using Explainable AI
1 Introduction
2 Explainable Artificial Intelligence
3 Dataset Description
4 Approach to the Proposed System
4.1 Support Vector Machine
4.2 Convolutional Neural Networks
4.3 ResNet50
4.4 Implementation of Explainable AI
5 Proposed Methodology
6 Results
7 Conclusion and Future Scope
References
Towards Helping Visually Impaired People to Navigate Outdoor
1 Introduction
1.1 Convolutional Neural Network
1.2 Visual Geometry Group
2 Literature
3 Methodology
3.1 Create the Dataset
3.2 Applying Existing Approach
3.3 Analyzing the Existing Approach
3.4 Detect Objects in Image
3.5 Train and Test the Model
3.6 Analyzing the Results
4 Experimentation
5 Conclusion and Future Work
References
An Analysis of Deployment Challenges for Kubernetes: A NextGen Virtualization
1 Introduction
2 Origin, History of Kubernetes, and the Community Behind
3 Related Works
3.1 Literature Review
3.2 Objective
4 Deployment of Application in Kubernetes Cluster in Public Cloud
4.1 Survey to Examine Kubernetes Impact
5 Analysis of Deployment Failure Strategies and Measures
6 Result Analysis
7 Result Analysis
8 Conclusion
References
A New Task Offloading Scheme for Geospatial Fog Computing Environment Using M/M/C Queueing Approach
1 Introduction
2 Related Work
3 Establishing the Model
4 Numerical and Simulation Examples
5 Conclusions and Future Work
References
Face Recognition Using Deep Neural Network with MobileNetV3-Large
1 Introduction
2 Related Work
3 Methodology
3.1 Dataset
3.2 Pre-processing
3.3 MobileNetV3Large Model
3.4 Hyperparameter Tuning
4 Result
5 Conclusion
References
Detection of BotNet Using Extreme Learning Machine Tuned by Enhanced Sine Cosine Algorithm
1 Introduction
2 Background and Related Work
2.1 BotNet and DDOS
2.2 Extreme Learning Machine
2.3 Population-Based Metaheuristics
3 Proposed Method
3.1 Suggested Improved SCA
4 Experiments and Discussion
4.1 Dataset Description, Pre-processing and Evaluation Metrics
4.2 Research Findings and Comparative Analysis
5 Conclusion
References
Cloud Services Management Using LSTM-RNN
1 Introduction
2 Related Work
3 Proposed Model
3.1 Forecast Utilizing LSTM-RNN
3.2 Workload Prediction Using LSTM Pseudocode
4 Result
5 Conclusion and Future Scope
References
Detection of Various Types of Thyroid-Related Disease Using Machine Learning
1 Introduction
2 Related Work
3 Proposed System
3.1 Dataset
3.2 Exploratory Data Analysis
3.3 Data Preprocessing
3.4 Training Phase
3.5 Testing the Model
4 Results and Discussion
5 Conclusion
References
Implementation of WSN in the Smart Hanger to Facilitate MRO Operations on Aircraft Fuselage Using Machine Learning
1 Introduction
2 Acquisition and Dataset
2.1 Complexity of Model and Training Dataset
2.2 Learning from Imbalanced Data
3 Existing Machine Learning Approaches
3.1 DNN (Deep Neural Networks)
3.2 Support Vector Machine (SVM)
3.3 Algorithmic Approach Using Minimal Data: Few-Shot Learning
4 State of the Art Method Evaluation
4.1 Experiment
4.2 Result
5 Proposed Approach
6 Conclusion and Prospects
References
Wi-Fi Controlled Smart Robot for Objects Tracking and Counting
1 Introduction
2 Related Work
3 Methodology
3.1 Wi-Fi Controlled Smart Robot Through Web Server
3.2 Proposed Methodology for Color Detection
3.3 Object Tracking for Counting Objects
4 Results and Discussion
5 Conclusion
References
Speech Recognition for Kannada Using LSTM
1 Introduction
2 Literature Review
3 Overview of LSTM and Kaldi
3.1 Markov Models
3.2 RNN
3.3 LSTM
3.4 Kaldi
4 Methodology
4.1 Audio Data Collection
4.2 Text Data Pre-processing
4.3 Feature Extraction and Preparing Language Models
4.4 Experiments with Monophone, Triphone Models
4.5 Experiments with DNN and LSTM
5 Results
6 Conclusion
References
Computer Vision-Based Smart Helmet with Voice Assistant for Increasing Driver Safety
1 Introduction
2 Related Works
3 Methodology
3.1 Deep Learning Model Development
3.2 Rear-End Collision Warning System
3.3 Deployment of Deep Learning Model via Server
3.4 Architecture of Helmet Software
3.5 Building Helmet (Hardware) Prototype
3.6 Comparison and Analysis of Models
4 Result
5 Conclusion and Future Scope
References
Predicting Aging Related Bugs with Automated Feature Selection Techniques in Cloud Oriented Softwares
1 Research Motivation and Aim
1.1 Imbalanced Data
1.2 High Dimensional Data
2 Related Work
3 Research Contributions
4 Research Framework
4.1 Automated Bug Report Extraction
4.2 Feature Selection Techniques
4.3 Datasets
4.4 Software Metrics
4.5 Imbalance Mitigation Procedure-SMOTE
4.6 Machine Learning Classifiers
4.7 Performance Measures
5 Experimental Setup
6 Results and Discussions
6.1 Detailed Analysis of Feature Ranking
6.2 Relative Comparison of Techniques
7 Conclusion
8 Threats to Validity and Future Work
References
Time Series Analysis of Crypto Currency Using ARIMAX
1 Introduction
2 Literature Review
3 Methodology
4 Components Taken into Consideration
4.1 Factors that Affect Crypto Currency
4.2 Dataset Used
4.3 ARIMAX Algorithm
5 Experimental Setup
5.1 Cointegrated Pair
5.2 Selection of Features
5.3 Building the Model
6 Result Analysis
7 Conclusion
References
A Machine Learning Approach Towards Prediction of User's Responsiveness to Notifications with Best Device Identification for Notification Delivery
1 Introduction
2 Related Work
3 Proposed System Architecture
3.1 Notification Module
3.2 User Identification Module
3.3 Active Device and Proximity Detection Module
3.4 Privacy and Access Control Module
3.5 Intelligent Delivery System Module
3.6 Notification Storage Bucket
4 Predicting User's Responsiveness to Notifications
4.1 Dataset
4.2 Predicting User's Responsiveness Using Machine Learning
5 Results and Discussions
6 Conclusion and Future Work
References
Real-Time Full Body Tracking for Life-Size Telepresence
1 Introduction
2 Related Work
3 Material and Method
3.1 Full-Body Tracking
3.2 Background Removal
3.3 Remote User Setting
4 Results and Discussion
5 Conclusion
References
Solar Power Generation Forecasting Using Deep Learning
1 Introduction
2 Use of Artificial Intelligence in Predicting Data
3 Methodology
3.1 Data Collection
3.2 Pre-processing
3.3 Split Data into Train and Testing Sets
3.4 Data Standardization
3.5 Building Model
3.6 Training Model
4 Model Building and Implementation
5 Model Evaluation
6 Results
7 Conclusion
References
Applications of Big Five Personality Test in Job Performance
1 Introduction
1.1 Dimensions of Job Performance
1.2 Personality Model with Five Traits
2 Literature Review
3 Objectives of the Study
4 Research Design
4.1 Measuring Instruments
5 Data Analysis Technique Employed
5.1 Exploratory Factor Analysis
5.2 Confirmatory Factor Analysis
6 Cluster Analysis
7 Results and Discussions
8 Conclusion and Future Works
References
Local Mean Decomposition Based Epileptic Seizure Classification Using Ensemble Machine Learning
1 Introduction
2 Methodology
2.1 Clinical Scalp EEG Dataset
2.2 Local Mean Decomposition (LMD)
2.3 Hjorth Parameters
2.4 Ensemble Machine Learning Algorithms
3 Result and Discussion
4 Conclusion
References
An Equilibrium Optimizer-Based Ensemble for Aspect-Level Sentiment Classification
1 Introduction
2 Background
2.1 Optimization for Feature Selection
2.2 Classifier Ensemble Reduction Using Feature Selection
2.3 Deep Learning-Based Ensemble for Aspect-Level Sentiment Classification
3 Proposed Methodology
3.1 Equilibrium Optimizer-Based Feature Selection (EO-FS)
3.2 EO-Based Ensemble Approach
4 Experimental Study
4.1 Dataset and Settings
4.2 Experimental Results
4.3 Statistical Test
5 Conclusion
References
Malware Detection Using Big Data and Deep Learning
1 Introduction
2 Related Work
3 Proposed Method
3.1 Dataset Used
4 Proposed System with Convolution Neural Network
5 Results
6 Discussion
7 Conclusion and Future Work
References
Review on the Static Analysis Techniques Used for Privacy Leakage Detection in Android Apps
1 Introduction
2 Literature Review for Static Analysis
3 Conclusion
References
Radon Transformation-Based Mammogram Image Classification
1 Introduction
2 Literature Work
3 Proposed Work
3.1 Preprocessing and Dataset Preparation
3.2 Radon Transformation and Feature Vector Creation
3.3 Experimental Results and Discussion
References
Unmanned Arial Vehicle as a Tool for Facemask Detection
1 Introduction
2 Related Work
3 Methodology
3.1 Images Augmentation and Pre-processing
3.2 The Proposed CNN Architecture
3.3 Drone Programming
4 Results
5 Conclusion
References
A Novel Ensemble Trimming Methodology to Predict Academic Ranks with Elevated Accuracies
1 Introduction
2 Work Done Till Now
3 Proposed Methodology
3.1 Handling Missing Data
3.2 Data Balancing
3.3 Data Normalization
3.4 Dataset Splitting
3.5 Model Trimming
3.6 Model Optimization
3.7 Model Prediction
4 Empirical Setup and Results
5 Comparison with State-Of-Art
6 Conclusion and Future Work
References
A Multiclass Tumor Detection System Using MRI
1 Introduction
2 Related Work
3 Proposed Methodology
3.1 Image Preprocessing
3.2 Tumor Segmentation
3.3 Data Augmentation
3.4 Tumor Detection
4 Dataset
5 Experiments and Results
5.1 Comparative Evaluation
5.2 Ensemble Model
6 Conclusion
References
Analysis on DeepFake Dataset, Manipulation and Detection Techniques: A Review
1 Introduction
2 DeepFake Datasets
3 DeepFake Generation
3.1 Type of Facial Manipulation
3.2 Manipulation Techniques
4 DeepFake Detection
4.1 Convolutional Neural Networks
4.2 Recurrent Neural Networks
4.3 Xception Neural Network
4.4 Capsule Networks
4.5 Vision Transformers
5 Literature Survey
6 Conclusion
References
Vituperative Content Detection: A Multidomain Architecture Using OpenCV
1 Introduction
2 Literature Survey
2.1 Drawback of Existing Systems
3 Proposed Methodology
3.1 Guns, Alcohol, Religious Flags and Cuss Gesture Detection Using YOLOv5
3.2 Detection of Cuss Words in Image Using Optical Character Recognition
4 Results
4.1 Qualitative Results
4.2 Performance Metrics and Quantitative Results
5 Conclusion and Future Scope
References
Paraphrase Generator Using Natural Language Generation and Natural Language Processing
1 Introduction
2 Literature Survey and Existing System
3 Proposed System
4 System Design
4.1 Methodology 1
4.2 Methodology 2
4.3 Methodology 3
4.4 Methodology 4
5 Module Description
5.1 Google PAWS
5.2 Features Extraction
6 Implementation
7 Analysis
8 Conclusion
References
An Investigational Study on Implementing Integrated Frameworks of Machine Learning and Evolutionary Algorithms for Solving Real-World Applications
1 Introduction
2 Related Works
3 The OaL and OtL Frameworks
3.1 The ‘Optimization After Learning (OaL)’ Framework
3.2 The ‘Optimization Together with Learning (OtL)’ Framework
4 The Experimental Setup
5 Results and Discussions
5.1 Validation of the ‘Optimization After Learning (OaL)’ Framework
5.2 Validation of the ‘Optimization with Learning Together (OtL)’ Framework
6 Conclusions and Future Enhancements
References
Deep Learning Based Cryptocurrency Real Time Price Predication
1 Introduction
2 Related Work
3 Proposed Work
3.1 Model Description
3.2 Dataset
3.3 Experiment Details
3.4 Evaluation Metrics
4 Result and Discussion
5 Conclusion
References
Secure Electronic Polling Process Utilizing Smart Contracts
1 Introduction
2 Related Works
3 Experimental Setup
3.1 Process
3.2 Implementation Tools
4 Results and Discussion
4.1 Security Analysis
5 Conclusion and Future Work
References
Machine Learning-Based Smart Waste Management in Urban Area
1 Introduction
1.1 Smart Trash Box
1.2 Waste Segregator
2 Problem Definition
2.1 In Smart Waste Management Systems, the Demand for Exact Emptying Detection is a Driving Force
2.2 Challenge in Waste Segregation for Recycling
3 Objective
4 Methodology of the Proposed Model
4.1 Designing for the Precision Waste Disposal from Dustbin
4.2 Designing for Segregation of Wastes for Proper Recycling
5 Future Works
6 Conclusion
References
Twenty V’s: A New Dimensions Towards Bigdata Analytics
1 Introduction
2 Evolution of 17 V’s of Bigdata Characteristics
2.1 Traditional Three V’s, Four Essential V’s, Five Oguntimilehin V’s of Bigdata
2.2 Most Important 10 V’s of Bigdata
2.3 Core 17 V’S of Bigdata
3 Another 3 New V’s of Bigdata Traits or Characteristics
3.1 Versatility
3.2 Vastness
3.3 Vaticination
4 Conclusion
References
A Computer Vision-Based Human–Computer Interaction System for LIS Patients
1 Introduction
2 Literature Review
3 Traditional Methods Used
3.1 EEG
3.2 EOG
3.3 Counting the Number of Blinks
4 Proposed Methodology
4.1 Face and Eye Detection
4.2 Intentional Blink Detection
4.3 Selecting Characters Using Eye Blink
4.4 Implementation Details
5 Observations and Results
5.1 Words Per Minute
6 Conclusion and Future Scope
References
Semantic Segmentation for Edge Devices—Survey and an End-to-End Readiness on the Target Platform
1 Introduction
2 Survey and Selection of Automotive Grade Semantic Segmentation Networks
3 Datasets
4 Edge Device Compliant Models
5 Conclusion and Future Scope
References
Performance Comparison of Machine Learning and Deep Learning Models in DDoS Attack Detection
1 Introduction
2 Literature Review
3 Proposed Approaches
3.1 Machine Learning
3.2 Deep Learning
3.3 Dataset
4 Proposed DDoS Attack Prediction Model
5 Result and Analysis
6 Conclusion
References
Application of Artificial Intelligence in Insurance Sector: A Bibliometric View
1 Introduction
2 Research Methodology and Data Collection
3 Data Analysis
3.1 Publication Growth Analysis
3.2 Journal Analysis
3.3 Authors Analysis
3.4 Most Global Cited Documents
3.5 Co-citation Analysis
3.6 Co-occurrence of Authors with Keywords
3.7 Most Cited Country and Country-Specific Production
3.8 Word Cloud
3.9 Thematic Evolution
4 Discussion and Conclusion
References
Evaluation of Stock Prices Prediction Using Recent Machine Learning Algorithms
1 Introduction
2 Literature Work
3 Applied Algorithms
3.1 Linear Regression
3.2 Support Vector Machine
3.3 Random Forest
3.4 Gradient Boosted Regressor
4 Materials and Methodology
5 Evaluation and Test Score of Algorithms
6 Conclusion and Future Scope
References
Deep Learning Techniques for Explosive Weapons and Arms Detection: A Comprehensive Review
1 Introduction
2 Dataset Discussion
3 Weapon Detection Approach
3.1 Two-Stage Target Detection Framework
3.2 One-Stage Target Detection Framework
4 Methodology: Weapon Detection System
5 Limitations of the Study
6 Future Work and Opportunities
6.1 Super Resolution
6.2 Transfer Learning
6.3 Zero-Shot Learning
6.4 Reinforcement Learning
6.5 Real-Time Weapon Specific Dataset
6.6 Real-Time Deployment of Models
7 Weapon Detection Potential Application
7.1 Law Enforcement in Hostile Stand-Off
7.2 Crime Identification Systems
7.3 Smart Surveillance Systems
8 Conclusion
References
Real-Time Implementation of Automatic License Plate Recognition System
1 Introduction
2 Related Work
3 Proposed System
3.1 Image Acquisition
3.2 Labeling Image
3.3 Training the Model
3.4 ONNX Format
3.5 Detection
3.6 Recognition
4 Results
4.1 Detection
4.2 Recognition
5 Future Scope
6 Conclusion
References
Deep Learning and Optical Character Recognition-Based Automatic UIDAI Details Extraction System
1 Introduction
2 Literature Survey
3 Proposed Methodology
3.1 Object Detection
3.2 Preprocessing
3.3 Recognition
4 Experimentation and Results
4.1 Detection
4.2 Recognition
5 Conclusion
5.1 Contribution
5.2 Future Scope
References
Comprehensive Dashboard for Alzheimer’s Disease Through Machine Learning
1 Introduction
2 Related Work
3 System Design
4 Methodology
4.1 Disease Prediction
4.2 Recommendation Based on User Input
5 Results and Discussion
6 Conclusion and Future Work
References
Empirical Study of Meta-learning-Based Approach for Predictive Mutation Testing
1 Introduction
2 Background of MT and PMT
3 Meta-learning
4 Empirical Data and Research Hypothesis
5 Data Modeling and Result Analysis
6 Statistical Testing and Conclusion
References
A Comparative Analysis of Transfer Learning-Based Techniques for the Classification of Melanocytic Nevi
1 Introduction
2 Related Work
3 Methodology
3.1 Dataset and Experimental Setup
3.2 Pre-processing Methods
3.3 The AlexNet Architecture
3.4 The VGGNet Architecture
3.5 The ResNet Architecture
3.6 The Inception V3 Architecture
3.7 The EfficientNet Architecture
3.8 Evaluation Metrics
4 Results and Discussion
5 Conclusion and Future Work
References
Machine Learning Using Radial Basis Function with K Means Clustering for Predicting Cardiovascular Diseases
1 Introduction
2 Literature Review
3 Comparison of Classification Approaches
4 Radial Basis Function
5 Proposed Methodology
5.1 Dataset Description
5.2 Normalization
5.3 Distribution of the Variables
6 Results and Discussions
7 Comparison with Existing Work
8 Conclusion and Future Work
References
Land Registry System Using Smart Contract of Blockchain Technology
1 Introduction
2 Background
2.1 Decentralization
2.2 Transparency
2.3 Immutability
2.4 P2P Network
2.5 Distributed Consensus
2.6 Smart Contract
3 Related Works
4 Proposed Model
5 Conclusion
References
An Image Based Harassment Detection System Using Emotion Feature Vector Based on MTCNN
1 Introduction
2 Related Work
3 Proposed Method
3.1 Problem Definition
3.2 Proposed Framework
4 Method Discussion
4.1 Person Detection Module
4.2 Emotion Recognition Modeling
4.3 Classification
5 Experiments
5.1 Dataset
5.2 Implementation
5.3 Result and Analysis
6 Conclusion and Future Work
References
Recent Advancement in Pancreatic Cancer Diagnosis Using Machine Learning-Based Methods: A Systematic Review
1 Introduction
2 Scope and Objectives
3 Benchmark Datasets
3.1 National Centre for Biotechnology Information—NCBI Dataset
3.2 Surveillance, Epidemiology, and End Results—SEER Dataset
3.3 The Cancer Imaging Archive—TCIA Dataset
3.4 Medical Segmentation Decathlon—MSD Dataset
3.5 Gene Expression Omnibus—GEO Database
3.6 The Cancer Genome Atlas—TCGA Database
3.7 Medical Image Computing and Computer-Assisted Intervention—MICCAI Dataset
3.8 11_Tumor Database
3.9 LHDB-NHIRD Dataset
4 Literature Selection Methodology
5 Literature Survey
6 Analysis and Discussion
7 Conclusion
References
Interactive Gaming Experience in VR Integrated with Machine Learning
1 Introduction
1.1 Unity3D
2 Proposed Idea
2.1 Unity 3D
3 Experimental Results
4 Limitations
5 Future Scope
6 Conclusion and Discussion
References
Comparative Analysis of U-Net-Based Architectures for Medical Image Segmentation
1 Introduction
2 U-NET Architecture
3 Related Work
4 Model Evaluation
5 Dataset and Experimental Setup
6 Comparative Analysis and Results
7 Conclusion and Future Work
References
Real-Time Fruit Detection and Recognition for Smart Refrigerator
1 Introduction
2 Related Work
3 The Proposed Method
3.1 Dataset Creation
3.2 Training
3.3 Testing
4 Experimental Data and Results
4.1 Figures and Tables of Results
5 Conclusion
References
MCDM Based Evaluation of Software Defect Prediction Models
1 Introduction
2 Related Work
3 Research Methods
3.1 Proposed Methodology
3.2 Machine Learning Techniques
3.3 Performance Measures
3.4 MCDM Method—Weighted Sum Model (WSM)
4 Experimental Study
4.1 Datasets
4.2 Experimental Design
5 Results and Discussion
5.1 Software Defect Prediction Results
5.2 MCDM Ranking
6 Conclusion
7 Future Scope
References
Leveraging Zero-Trust Architecture for Improving Transaction Quality of Financial Services Using Locational Data
1 Introduction
1.1 Motivation
1.2 Scope of Work
2 Literature Survey
2.1 Survey of Existing System
2.2 Research Gap
3 Proposed System
3.1 Zero-Trust Security
3.2 Architecture
3.3 Zero-Trust Evaluation
4 Software Requirements
5 Results and Discussions
6 Conclusion and Future Work
References
Mobile Computing Based Security Analysis of IoT Devices
1 Introduction
1.1 Mobile Computing
1.2 Motivation
1.3 Objectives
2 Literature Review
3 Problem Statement
3.1 Applications
3.2 Threats
4 Proposed Architecture
5 Implementation
6 Result and Analysis
7 Conclusion and Future Work
References
Abusive Content Detection on Social Networks Using Machine Learning
1 Introduction
2 Background Work
2.1 Why Is This Task So Challenging?
3 Hate Speech and Abusive Content on Social Networks
4 Methodology and Implementation
4.1 Dataset
4.2 Experimental Setup
5 Result and Inferences
6 Conclusion and Future Scope
References
Ultrasound Nerve Image Segmentation Using Attention Mechanism
1 Introduction
2 Literature Review
3 Research Gaps
4 Methods
4.1 U-Net
4.2 Attention Guided U-Net
4.3 Attention Guided ResU-Net
5 Experiments
5.1 Dataset Description
5.2 Evaluation Metrics
5.3 Implementation Details
5.4 Results and Discussion
6 Conclusion and Future Work
References