
The Future of Artificial Intelligence and Robotics
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This book includes the results from the 5th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR), held in National Institute of Technology, Kurukshetra, on December 07-09, 2023, which brought together visionaries, researchers, and industry leaders at the forefront of technological innovation. In the rapidly evolving landscape of technology, deep learning, artificial intelligence, and robotics stand as a beacon of innovation and intellectual exchange. Among the myriad of groundbreaking contributions, a notable gem emerges-a forthcoming book that promises to encapsulate the essence of the 5th International Conference on Deep Learning, Artificial Intelligence and Robotics, (ICDLAIR) 2023 proceedings. Titled " Progress in AI-Driven Business Decisions & Robotic Process Automation," this publication is poised to become a cornerstone for enthusiasts, researchers, and professionals seeking a comprehensive understanding of the latest advancements in deep learning, artificial intelligence, and robotics.
Focused on the theme "Progress in AI-Driven Business Decisions & Robotic Process Automation," the conference showcased groundbreaking developments in the field, exploring the intersection of deep learning, artificial intelligence (AI), and robotics.
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Content
- Intro
- Contents
- A Comparative Study of Machine Learning Algorithms for Predicting Cardiovascular Disease
- 1 Introduction
- 2 Related Works
- 2.1 Supervised Machine Learning-Based Approaches
- 2.2 Unsupervised Machine Learning-Based Approaches
- 2.3 Hybrid Machine Learning-Based Approaches
- 3 Methodology and Study Design
- 4 Experiments and Discussions
- 4.1 Experiments: Setup and Datasets
- 4.2 Discussions: Performance Evaluation
- 5 Conclusion
- References
- Deep W-Net: DNN for Spatial Saliency Prediction in Video Frames
- 1 Introduction
- 2 Related Work
- 2.1 Recent Work
- 3 Proposed Model
- 3.1 Proposed Architecture
- 3.2 Encoder Block
- 3.3 Decoder Block
- 3.4 Training Process
- 4 Experimental Results
- 4.1 Evaluation Methodology
- 4.2 Comparative Research Employing Techniques that Are Already Proposed
- 5 Conclusion
- References
- Optimal Pose Estimation with Particle Filters Using Unpowered Wheels
- 1 Introduction
- 2 Literature Review
- 3 Problem Statement
- 4 Error Analysis in Conventional Approaches
- 4.1 GPS Based Path Tracking Analysis
- 4.2 Wheel Odometry Data-Based Path Tracking Analysis
- 5 Improved Path Tracking Technique
- 6 Conclusion
- References
- A Short Survey on Comparative Study of Modern Cryptography Approach
- 1 Introduction
- 1.1 Cryptography Goals
- 1.2 Cryptography Algorithm
- 1.3 Applications of Cryptography
- 1.4 Aims and Objectives of the Study
- 1.5 Structure of the Paper
- 2 Background
- 2.1 History of Cryptography
- 2.2 Short Overview of Classic to Modern Cryptography Path
- 2.3 Basic Terminology of Cryptography
- 2.4 Cryptography Attacks
- 2.5 Related Work
- 3 Comparative Study of Modern Cryptography
- 3.1 Symmetric Encryption
- 3.2 Asymmetric Encryption
- 3.3 Hashing
- 4 Conclusion
- References
- Advances in Computer-Aided Detection and Diagnosis of Retinal Diseases: A Comprehensive Survey of Fundal Image Analysis
- 1 Introduction
- 2 Literature Review
- 2.1 Data Acquisition
- 2.2 Data Pre-processing and Feature Selection
- 2.3 Techniques Used
- 3 Critical Evaluation
- 4 Conclusion
- References
- Driver Safety and Drowsiness Detection in Internet of Vehicles with Federated Learning
- 1 Introduction
- 2 Related Work
- 3 Proposed Method
- 4 Results and Discussion
- 4.1 Tools Used and Dataset
- 4.2 Vehicle Network Simulation
- 5 Conclusion and Future Work
- References
- Privacy Preserving Fingerprint Classification Using Federated Learning
- 1 Introduction
- 2 Related Work
- 3 Proposed Solution
- 4 Results and Discussion
- 4.1 Network Architecture
- 4.2 Training Setup
- 4.3 Authentication Results
- 5 Conclusion and Future Direction
- References
- Comparative Study of Ensemble Learning Models for Smart Meter Load
- 1 Introduction
- 2 Literature Review
- 3 Ensemble Learning Based Forecasting Model
- 4 Results and Discussion
- 4.1 Experimental Setup and Dataset
- 4.2 Performance Analysis
- 5 Conclusion
- References
- Social-Media Video Summarization Using Convolutional Neural Network and Kohnen's Self Organizing Map
- 1 Introduction
- 2 Related Work
- 3 Proposed Model
- 3.1 Pre-processing
- 3.2 Feature Extraction
- 3.3 SOM Clustering
- 3.4 Keyframe Selection
- 4 Experimental Results and Discussion
- 4.1 Experimental Settings
- 4.2 Dataset
- 4.3 Evaluation Metrics
- 4.4 Results Analysis
- 5 Conclusion
- References
- Machine Learning and Deep Leaning in Predicting Coronary Heart Disease
- 1 Introduction
- 2 Research Methodology
- 2.1 Collection and Properties of Dataset
- 2.2 Data Pre-processing
- 3 Experiment and Output
- 4 Conclusion
- 5 Future Works
- References
- Augmented Super Resolution GAN (ASRGAN) for Image Enhancement Through Reinforced Discriminator
- 1 Introduction
- 2 Super Resolution
- 3 Proposed Method
- 4 Results and Findings
- 5 Conclusion
- References
- Convolutional Block Attention Assisted Dense Stacked Bi-LSTM for the Generation of RDF Statements
- 1 Introduction
- 2 Related Works
- 3 Proposed Methodology
- 3.1 Pre-processing
- 3.2 Feature Extraction Using the BERT-LSTM Model
- 3.3 Feature Clustering Using Adaptive Density K-means Clustering
- 3.4 RDF Classification Using Convolutional Block Attention Assisted Dense Stacked Bi-LSTM Model
- 4 Results and Discussion
- 4.1 Dataset Description
- 4.2 Performance Measures
- 4.3 Performance Analysis
- 4.4 Discussion
- 5 Conclusion
- References
- Real-Time Permanent Change Proposals for Abandoned Object Detection
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 4 Experiment Results
- 4.1 Accuracy Results
- 4.2 Accuracy Comparison
- 4.3 Runtime Speed Analysis
- 5 Conclusion
- 6 Future Work
- References
- An Excursion to Ontology-Based Non-functional Requirements Specification
- 1 Introduction
- 2 Non-functional Requirements
- 3 Quality Models
- 4 Ontology
- 5 NFRs Specification
- 5.1 NFRs: A Hard or Soft Goal?
- 5.2 NFRs Extraction: Interview-Based Approach to Ontology-Based Approach
- 5.3 Comparative Analysis and Issues
- 6 Conclusions
- References
- A Review of Traditional and Neural Network Methods for Protecting Privacy in Big Data Analytics
- 1 Introduction
- 2 Anonymization Techniques
- 3 Data Distribution Technique
- 3.1 Horizontal Distribution
- 3.2 Vertical Distribution
- 4 Randomization Technique
- 5 Privacy Preserving Neural Networks
- 5.1 Cloud-Based Neural Networks
- 5.2 Clustering Based Algorithms
- 6 Privacy Preservation Using Fuzzy Neural Network
- 7 Conclusion
- References
- A Long Short-Term Memory Learning Based Malicious Node Detection for Clustering in Wireless Sensor Networks
- 1 Introduction
- 2 Related Work
- 3 Proposed System Architecture
- 3.1 Parameter Tuning, and Evaluation Metrics
- 4 Results and Discussions
- 5 Conclusion
- References
- Experimental Analysis for Sensor Reduction to Depict Real-Time Applications Through Regression Techniques
- 1 Introduction
- 2 Related Work
- 3 Proposed Methodology
- 3.1 Regression Technique
- 3.2 Mathematical Model
- 4 Experiments and Results
- 5 Conclusion
- References
- Multi-resolution Neural Network for Road Scene Segmentation
- 1 Introduction
- 2 Related Works
- 3 Proposed Work
- 3.1 Proposed Neural Network
- 3.2 Dataset
- 3.3 Benchmarking
- 4 Results and Discussion
- 4.1 Discussion
- 5 Conclusion
- References
- A CNN-Based Road Accident Detection and Comparison of Classification Techniques
- 1 Introduction
- 1.1 Motivation
- 1.2 Objective
- 1.3 Contribution
- 1.4 Paper Organization
- 2 Related Works
- 2.1 Machine Learning Methods
- 3 Proposed Work
- 3.1 Feature Extraction by CNN
- 3.2 Architecture Used
- 4 Results and Analysis
- 5 Conclusion and Future Work
- References
- Football Match Result Prediction Using Twitter Statistical/Historical Data
- 1 Introduction
- 1.1 Motivation
- 1.2 Objective
- 1.3 Contribution
- 2 Literature Survey
- 3 Methodology
- 3.1 Datasets
- 3.2 Training and Testing Splitting
- 3.3 Models Used
- 3.4 Evaluation Matrices
- 4 Results and Discussion
- 4.1 Random Forest Classifier
- 4.2 SVM Classifier
- 4.3 Naive Bayes Classifier
- 4.4 KNN Classifier
- 4.5 Comparison of all Models Used
- 4.6 Comparison with Existing Models
- 5 Conclusion and Future Work
- References
- Safeguarding Ecosystems and Efficiency in Peer-to-Peer File Sharing Systems: An IoT-Inspired Approach to Pollution Mitigation
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 4 Experiments and Results
- 4.1 Analysis
- 4.2 Impact
- 5 Conclusion
- References
- A Heuristic for Minimizing Resource Requirement for Quantum Graph Neural Networks
- 1 Introduction
- 2 Related Work
- 3 Preliminaries
- 3.1 GNNs for Graph Classification
- 3.2 Quantum Circuits
- 3.3 Hybrid-QGNNs for Graph Classification
- 3.4 Clustering Algorithms
- 4 Methodology
- 4.1 Parameter Training
- 4.2 Classification
- 5 Experiments and Results
- 6 Conclusion
- References
- Light-Gated Recurrent Unit Based Acoustic Modeling for Improved Hindi ASR
- 1 Introduction
- 2 DNN-Li-GRU Hybrid Architecture
- 3 Corpus Details and Experimental Setup
- 3.1 Corpus Details
- 3.2 Experimental Setup
- 4 Experiments
- 4.1 Experiment with Different Acoustic Features
- 4.2 Role of Batch-Normalization
- 4.3 Impact of Diffent Techniques
- 4.4 Computational Efficiency of Different Models
- 4.5 Hybrid Acoustic Modeling
- 5 Conclusion
- References
- Detecting Phishing URLs Using Machine Learning: A Review
- 1 Introduction
- 2 Literature Review
- 3 Issues and Challenges
- 3.1 Datasets and Insufficient Training Data
- 3.2 Dynamic and Changing Nature of Phishing Techniques
- 3.3 Feature Extraction Challenges
- 3.4 Class Imbalance
- 4 Future Research Directions
- 4.1 Improved Feature Extraction and Selection
- 4.2 Better Training Data
- 4.3 Hybrid Approaches
- 4.4 Integration with User Education
- 5 Conclusion
- References
- Comparative Analysis of Pneumonia Detection from Chest X-ray Using Deep Learning
- 1 Introduction
- 1.1 Transfer Learning
- 1.2 Ensemble Learning
- 2 Available Datasets
- 3 Issues with Datasets
- 4 Comparative Analysis of Pneumonia Detection Approaches
- 5 Role of Pre-processing in Deep Learning
- 6 Discussion and Comparative Analysis
- 7 Conclusion
- References
- Forging Futures: Empowering Decentralised AI Marketplaces Through Blockchain Innovation
- 1 Introduction: Decentralized Artificial Intelligence Marketplace Bridging Innovation and Trust
- 2 What is Decentralized AI Marketplace?
- 2.1 The Decentralised Artificial Intelligence Market Seeks to Address These Issues by
- 3 Blockchain and Smart Contracts
- 3.1 Immutable Record Keeping
- 3.2 Smart Contract Automation
- 4 Data Monetization and Ownership
- 4.1 Data Sovereignty and Control
- 4.2 Tokenized Data Exchange
- 4.3 Fair Compensation
- 5 Federated Learning and Privacy in a Decentralized AI Marketplace
- 5.1 Federated Learning: A Decentralized Approach to Learning
- 6 Dynamic Pricing and Allocation of Resources in a Decentralised Artificial Intelligence Marketplace
- 6.1 Dynamic Pricing Mechanisms
- 6.2 User-Centric Pricing
- 6.3 Obstacles and Considerations
- 7 Decentralized Governance Models AI
- 7.1 Decentralized Autonomous Organizations (DAOs)
- 7.2 Consensus Mechanisms for Governance
- 7.3 Compliance and Governance in the Field of Regulation
- 8 Cross-Chain Interoperability
- 8.1 Key Aspects
- 9 Challenges and Solutions in Decentralized AI Marketplaces
- 9.1 Scalability
- 9.2 Quality Assurance
- 9.3 Data Privacy and Ownership
- 10 Case Study - Ocean Protocol
- 10.1 Data Assets Representation
- 10.2 Smart Contracts
- 10.3 Compute-To-Data (C2D)
- 10.4 Data Monetisation
- 10.5 Decentralised Governance Mechanisms
- 11 Conclusion
- References
- Citrus Leaf Disease Prediction: Deep Feature Fusion Perspective
- 1 Introduction
- 1.1 Contributions
- 1.2 Organisations
- 2 Related Work
- 3 Material and Methodology
- 3.1 About Dataset
- 3.2 Methodology
- 4 Result and Discussion
- 5 Conclusion
- References
- Badminton Shot Recognition with LSTM Network
- 1 Introduction
- 2 Related Work
- 3 Proposed Methodology
- 3.1 Dataset Collection
- 3.2 Video Augmentation and Labelling
- 3.3 Key-Point Detection
- 3.4 Classification Model
- 4 Experiments and Results
- 5 Conclusion
- References
- An Ensemble Learning Model for Automatic Detection of Cyberbullying on Instagram Platform
- 1 Introduction
- 2 Related Works
- 3 Proposed System
- 3.1 Pre-processing of Data
- 3.2 Detection Model Using Supervised Machine Learning Algorithm
- 4 Experimental Results
- 4.1 Description of Dataset
- 4.2 Performance Evaluation Metrics
- 5 Conclusion and Future Enhancement
- References
- Enhancing Plant Pathology Detection and Stratification with a Tailored Mask R-CNN Framework
- 1 Introduction
- 2 Literature Survey
- 3 Proposed Methodology
- 4 Results and Discussions
- 4.1 Dataset Description
- 4.2 Quantitative Metrics
- 4.3 Performance Evaluation Metrics
- 4.4 Performance Evaluation
- 4.5 Computation Time
- 5 Conclusion
- References
- Deep Neural Network Regression Based Device Free Localization Technique in Changing Indoor Environment
- 1 Introduction
- 2 Proposed Link Distance Deep Neural Network (LD-DNN) Regression Based DFL Technique
- 2.1 A System Architecture of Proposed LD-DNNR Model in Real Time Scenario
- 3 Deep Neural Network Regression Model
- 3.1 MLP Based Deep Neural Network Regression
- 4 Results and Discussion
- 4.1 Experimental Setup
- 4.2 Performance Metrics
- 4.3 Performance Comparison of the Proposed LD-DNNR Based DFL Technique with Benchmark Models
- 4.4 Performance of Proposed LD-DNNR Based DFL Technique in Changing Indoor Environment
- 5 Conclusion
- References
- An Ensemble-Based Approach for Cyber Attack Detection in Financial Systems
- 1 Introduction
- 2 Background Study
- 2.1 Digital Transaction and Payment Methods
- 2.2 Online Transaction System
- 2.3 Digital Payment Fraud
- 3 Methodology
- 3.1 Operational Flow
- 4 Result and Analysis
- 4.1 Formulation
- 5 Conclusion
- References
- LoHCEO (Low Overhead and High Congestion Reduction in Epidemic Mode for Opportunistic Networks)
- 1 Introduction
- 2 Contextual and Associated Work
- 2.1 Epsoc: Social-Based Epidemic-Based Routing Protocol in Opportunistic Mobile Social Network
- 2.2 Enhanced Epidemic Routing Protocol in Delay Tolerant Networks
- 2.3 Analysis of Epidemic, PROPHET and Spray and Wait Routing Protocols in the Mobile Opportunistic Networks
- 2.4 Congestion Control for Epidemic Routing in Opportunistic Networks
- 2.5 Buffer Adaptive Epidemic Protocols for DTN
- 2.6 Prioritized Epidemic Routing for Opportunistic Networks
- 3 Proposed Work
- 3.1 Apprehension of Network Configuration
- 4 Result Discussion
- 4.1 Packet Transfer Ratio (PDR)
- 4.2 Packet Overhead Ratio
- 4.3 Packet Transmission Delay
- 5 Conclusion and Future Work
- References
- MetaMis: A Study of Identifying Missed Labels or Mislabels of Chest Radiographic Images Using Meta Learning
- 1 Introduction
- 1.1 Missed diagnosis
- 2 Related Work
- 3 Methods
- 3.1 Chest Radiographies
- 3.2 AI and Meta Learning Algorithms
- 3.3 Statistical analysis
- 4 Statistical Analysis
- 5 Discussion
- 6 Conclusion
- References
- An Automatic Process of Online Handwriting Recognition and Its Challenges
- 1 Introduction
- 2 Online Handwriting Recognition Systems
- 3 Challenges in Case of Online Handwriting Recognition
- 4 Challenges Based on Writer's Category and Vocabulary Type
- 5 Conclusion
- References
- IoT-Enabled Smart Restaurant Management System
- 1 Introduction
- 2 Existing Literature
- 2.1 Restaurant Management Systems
- 2.2 Fire Prevention Systems
- 3 Proposed System
- 3.1 Fire Safety
- 3.2 Food Ordering
- 3.3 Face Recognition System
- 4 Performance Analysis
- 4.1 Design for Hardware Fault Tolerance
- 4.2 Design for Network Fault Tolerance
- 4.3 Design for Performance
- 4.4 Design for Maintenance
- 4.5 Unit Testing
- 5 Conclusion
- References
- Design Framework for Building Smart Shopping Stores Using IoT
- 1 Introduction
- 2 Existing Literature
- 3 Proposed Framework
- 3.1 Smart Shopping Cart
- 3.2 Automated Billing Counter
- 3.3 Inventory Management
- 3.4 Sensor-Enabled Exit Gate
- 4 Results Analysis and Discussion
- 5 Conclusion
- References
- A Multi-objective Virtual Machine Placement Optimization in Sustainable Cloud Environment
- 1 Introduction
- 2 Related Work
- 3 Proposed Model
- 3.1 Resource Utilization
- 3.2 Energy Consumption
- 3.3 Carbon Footprint
- 4 NSGA II Based VM Allocations
- 4.1 Time Complexity Analysis
- 5 Performance Evaluation
- 5.1 Experimental Set-Up
- 5.2 Results
- 5.3 Comparative Analysis in Dynamic VMP
- 6 Conclusion
- References
- Fake News Detection Using Heterogeneous Information from Multimedia Content
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 3.1 Visual Model for Feature Map Extraction
- 3.2 Lingual Model For Embedding Extraction
- 3.3 Fusion of Visual and Lingual Features
- 4 Dataset and Experiments
- 4.1 Dataset
- 4.2 Experimental Results and Analysis
- 5 Conclusion and Future Work
- References
- Comparative Analysis of CNN and Transformers on Malicious Intent Detection in HTTP
- 1 Introduction
- 2 Literature Review
- 3 The Proposed Work
- 3.1 Overall Workflow and Process
- 3.2 Dataset Details
- 3.3 Data Preprocessing
- 3.4 Generate Embeddings
- 3.5 Visualisation
- 3.6 Deep Learning Models
- 4 Results and Discussion
- 4.1 More Findings
- 5 Conclusion
- References
- Comparison of Sensor-MAC (S-MAC), Timeout-MAC (T-MAC), Berkeley-MAC (B-MAC), and Modified ML-MAC (M2L-MAC) for Wireless Sensor Networks
- 1 Introduction
- 1.1 Motivation
- 1.2 Contributions
- 1.3 Organization of Paper
- 2 Literature Survey
- 3 Proposed Methodology
- 4 Simulation Results
- 4.1 Evaluation of Network Longevity
- 4.2 State of the Art Techniques
- 5 Conclusions
- References
- Automatic Code Scraping Based Test Case Generation
- 1 Introduction
- 1.1 Motivation
- 1.2 Organization of the Paper
- 2 Related Work
- 3 Problem Statement
- 4 Proposed Work
- 4.1 Abstract Syntax Tree (AST) Generation
- 4.2 AST Traversal
- 4.3 Test Case Generation
- 4.4 Test Case Prioritization
- 4.5 Cyclomatic Complexity for Coverage Analysis
- 4.6 Decision Points Detection
- 5 Result Analysis
- 6 Conclusion
- References
- Prediction of AQI for Urban Metropolis Using MLSTM-GRU Model
- 1 Introduction
- 1.1 Organization of the Paper
- 2 Related Work
- 3 Proposed Work
- 3.1 Collection and Description of Dataset
- 3.2 Preprocessing and Visualization of Data
- 3.3 Feature Selection
- 3.4 Modified LSTM-GRU (MLSTM-GRU) Model
- 4 Result and Discussion
- 4.1 Performance Evaluation Metrics
- 4.2 Experimental Result and Comparative Analysis
- 5 Conclusion and Future Scope
- References
- Land Use Land Cover Classification Using Multi-spectral Satellite Imagery
- 1 Introduction
- 2 Related Work
- 3 Datasets
- 4 Proposed Work
- 4.1 Design Methodology
- 4.2 System Architecture Diagram
- 4.3 Description of Algorithms
- 5 Result Analysis
- 6 Conclusion
- References
- An Ensemble Learning Based Career Prediction Model
- 1 Introduction
- 1.1 Contribution
- 1.2 Organisation
- 2 Proposed Model
- 2.1 Data Collection
- 2.2 Data Pre-processing
- 2.3 Ensemble Classification and Classifiers
- 3 Operational Summary
- 4 Results and Discussion
- 4.1 Experimental Setup and Data Set
- 4.2 Performance Analysis
- 5 Conclusion
- References
- Feature Extraction Analysis in a Speaker Identification System
- 1 Introduction
- 1.1 About the Paper
- 1.2 Motivation
- 1.3 Novelty and Contributions
- 2 Literature Survey
- 3 Proposed Methodology
- 3.1 MFCC
- 3.2 BFCC
- 3.3 GFCC
- 3.4 LPC
- 3.5 GMM
- 4 Experimental Setup
- 4.1 Dataset Used
- 4.2 Training Model
- 5 Results and Outcomes
- 6 Discussions and Future Aspects
- 7 Conclusion
- References
- Breast Cancer Prognosis Based on Machine Learning Model
- 1 Introduction
- 2 Literature Exploration
- 3 Materials and Methods
- 3.1 Preprocessing of Image
- 3.2 Feature Extraction
- 3.3 Naïve Bayes
- 3.4 Decision Tree (DT)
- 3.5 Logistic Regression (LR)
- 3.6 Random Forest (RF)
- 3.7 K-Nearest Neighbour (KNN)
- 3.8 Support Vector Machine (SVM)
- 4 Result and Discussion
- 5 Conclusion
- References
- PRESENT Block Cipher Defined over Galois-Field (28)
- 1 Introduction
- 2 Related Work
- 3 Proposed Method
- 3.1 S-Box Layer
- 3.2 Permutation Layer
- 3.3 Key Schedule
- 4 Statistical Testing
- 5 Performance Analysis
- 5.1 Security
- 5.2 Resource Requirement
- 6 Conclusion
- References
- Mammograms Image Quality Enhancement Using Center Adaptive Median Filter (CEAMF) for Noise and Artifact Removal
- 1 Introduction
- 1.1 Motivation and Research Gaps
- 2 Related Work
- 3 Proposed Work
- 3.1 Image Dataset
- 3.2 Methodology
- 3.3 Performance Metrics
- 4 Results Analysis
- 5 Conclusion
- References
- Fertilizer Recommendation with Stress Monitoring in Agriculture
- 1 Introduction
- 2 Literature Survey
- 3 Proposed Methodology
- 3.1 Statistical Analysis
- 3.2 Fertilizer Recommendation
- 4 Experimental Results
- 4.1 Dataset
- 4.2 Evaluation Metrics
- 4.3 Discussion on Results
- 5 Conclusion and Future Scope
- References
- Surface Water Mapping and Analysis in SANGAMAM of River Godavari and Krishna Rivers Using Google Earth Engine
- 1 Introduction
- 2 Literature Review
- 3 Methodology
- 3.1 Description
- 3.2 Architecture Diagram
- 3.3 Description
- 3.4 Description of Algorithms
- 4 Experimental Results
- 5 Conclusion
- References
- Spyware Alert System and Image Steganography for Military Application
- 1 Introduction
- 2 Literature Review
- 3 Proposed Method
- 3.1 Architecture Diagram
- 3.2 Description of Algorithms
- 3.3 Spyware Detection through Alert Message using Regular Expression
- 4 Results and Observations
- 4.1 Result and Analysis of Image Steganography
- 5 Conclusion
- References:
- Abstract. A Review on YOLO Algorithms for Social Distancing
- 1 Introduction
- 1.1 Motivation
- 2 Related Works
- 3 Research Model for Social Distancing
- 4 Problems, If Not Maintaining Social Distance
- 5 Object Detection and Tracking Model
- 5.1 Object Detection
- 5.2 Object Tracking
- 6 Deep Learning Based Object Detection
- 6.1 You Only Look Once (YOLO V6)
- 6.2 You Only Look Once (YOLO V7)
- 7 Results and Comparisons
- 8 Conclusion
- References
- A Hybrid Approach for Detecting Software Refactoring Sequencing
- 1 Introduction
- 1.1 Refactoring Sequencing
- 1.2 Hybridization of Algorithms
- 2 Research Methodology
- 3 Conclusions
- References
- ADNet: An Attention Embedded DenseNet121 Model for Weed Classification
- 1 Introduction
- 2 Related Work
- 3 Proposed Methodology
- 3.1 Dataset
- 3.2 Data Preprocessing
- 3.3 Architecture of the Proposed ADNet Model
- 4 Experiment Results
- 4.1 Experiment Setup
- 4.2 Dataset Preparation
- 4.3 Performance Analysis of Proposed CNN Models
- 4.4 Performance Comparison with Existing Research Work
- 5 Conclusion
- References
- NRASV: Noise Robust ASV System for Audio Replay Attack Detection
- 1 Introduction
- 1.1 Related Work
- 2 Proposed Approach
- 2.1 Feature Extraction
- 2.2 Classification
- 3 Experiments and Result Analysis
- 3.1 Performance of Proposed Model Under Clean Environment
- 3.2 Performance of Proposed Model Under Noisy Environment
- 4 Discussion and Comparative Analysis
- 5 Conclusion
- References
- Machine Learning for the Proactive Identification of Polycystic Ovary Syndrome (PCOS): Empowering Women's Health
- 1 Introduction
- 2 Literature Review
- 3 Methodology
- 3.1 Data Set
- 3.2 Data Analysis and Visualization
- 3.3 Data Preprocessing
- 3.4 Selection and Training the Model
- 3.5 Hyperparameter Tuning
- 4 Result and Discussion
- 5 Conclusion
- References
- RADU-Net: A Fully Convolutional Neural Network for Efficient Skin Lesion Segmentation
- 1 Introduction
- 2 Related Work
- 3 Proposed Method
- 3.1 Convolutional Block
- 3.2 The Encoder Path
- 3.3 The Connecting Bridge
- 3.4 The Decoder Path
- 3.5 Residual Connection
- 3.6 Attention Gates
- 4 Experimental Analysis
- 4.1 Dataset
- 4.2 Data Preparation and Augmentation
- 4.3 Experimental Setup
- 4.4 Evaluation Metrics
- 5 Results and Discussion
- 5.1 Ablation Study
- 5.2 Quantitative Performance Analysis
- 5.3 Qualitative Performance Analysis
- 6 Conclusion
- References
- Smart Healthcare AI-Infused Saline Monitoring System with IoT- Empirical Study
- 1 Introduction
- 2 Literature Review
- 3 Comparative Study Based on Literature Review
- 4 Conclusion
- References
- Music Recommendation System Using Psychological Scale
- 1 Introduction
- 1.1 Our Contributions
- 2 Related Work
- 3 Proposed Work
- 3.1 Data Collection
- 3.2 TIPI Scale
- 3.3 Dataset Description
- 3.4 Data Preprocessing
- 3.5 Recommendation Generation
- 4 Result Analysis
- 5 Conclusion
- References
- Bidirectional Long-Short Term Memory Based Approach for Sampling in Dual Arm Locomotion
- 1 Introduction
- 2 Related Work
- 3 Proposed Work
- 3.1 Dataset Generation
- 3.2 Finding Solution to the Dataset Using RRT*
- 3.3 Training of the Bi-directional Long Short Term Memory Projector
- 3.4 Goal Biased Sampling
- 3.5 Bi-LSTM Projector Architecture
- 3.6 Path Length and Time Required
- 3.7 Setup
- 4 Results Analysis
- 5 Conclusion
- References
- Decoding Emotions: Unveiling Sentiments and Sarcasm Through Text Analysis
- 1 Introduction
- 1.1 Background and Motivation
- 1.2 Problem Definition
- 1.3 Problem Objectives
- 2 Literature Survey
- 2.1 Sentiment Analysis
- 2.2 Sarcasm Detection
- 3 Material and Proposed Methods
- 3.1 Dataset Overview
- 3.2 Proposed Methods Used for Sentiment Analysis and Sarcasm Detection
- 3.3 Overall Workflow of Proposed Methodology and Implementation
- 4 Results and Discussion
- 4.1 Sentiment Analysis
- 4.2 Sarcasm Detection
- 5 Conclusion and Future Scope
- References
- Rice Disease Identification Using Vision Transformer (ViT) Based Network
- 1 Introduction
- 2 Related Works
- 3 Rice Disease Dataset
- 4 Proposed Network Architecture
- 5 Results and Discussion
- 6 Conclusion
- References
- Image Based Rice Weed Identification Using Deep Learning and Attention Mechanisms
- 1 Introduction
- 2 Methodology
- 2.1 Dataset
- 2.2 Data Pre-processing
- 2.3 Model Architecture
- 2.4 Hyperparameters
- 2.5 Experimental Implementation
- 3 Results and Discussion
- 3.1 Evaluation Metrics
- 4 Conclusion
- References
- Intrusion Detection System Using Deep Learning Techniques for Internet of Medical Things (IoMT)
- 1 Introduction
- 2 Related Work
- 3 Dataset Description
- 4 Experimental Setup
- 5 Research Methodology
- 5.1 Preprocessing
- 5.2 Research Model
- 5.3 Performance Metrics
- 6 Results and Analysis
- 7 Conclusion and Future Scope
- References
- Detection and Grading of Diabetic Retinopathy from Fundus Images by Applying Transfer Learning
- 1 Introduction
- 2 Motivation
- 3 Literature Survey
- 4 Proposed Work
- 4.1 Dataset Description
- 4.2 Preprocessing
- 4.3 Data Augmentation
- 4.4 Implementation
- 5 Results and Analysis
- 5.1 Results and Comparison
- 5.2 Performance Comparison
- 6 Conclusion and Future Plan
- References
- Indian Sign Language Bilateral Translator
- 1 Introduction
- 2 Related Work
- 3 Proposed Work
- 3.1 English Text to Indian Sign Language Translation
- 3.2 Indian Sign Language to English Text
- 4 Result
- 4.1 English Text to Indian Sign Language Translation
- 4.2 Indian Sign Language to English Text
- 5 Conclusion and Future Scope
- References
- A Review on Security Challenges: Cryptography and Blockchain for Internet of Things
- 1 Introduction
- 2 Security Challenges in IoT
- 3 Cryptography in IoT Security
- 3.1 Data Encryption
- 3.2 Authentication and Key Management
- 4 Blockchain Technology for IoT Security
- 5 Integration of Cryptography and Blockchain
- 6 Future Directions and Challenges
- 6.1 Emerging Trends
- 6.2 Ongoing Challenges
- 7 Conclusion
- References
- Current Approaches and Challenges in Medical Image Analysis and Visually Explainable Artificial Intelligence as Future Opportunities
- 1 Introduction
- 2 Popular Visual Sources of Medical Diagnosis
- 3 Deep Learning and Machine Learning Approaches in the Medical Domain
- 4 Challenges of Deep Learning and Machine Learning
- 5 XAI Model
- 6 Conclusion
- References
- Early Detection and Classification of Zero-Day Attacks in Network Traffic Using Convolutional Neural Network
- 1 Introduction
- 2 Related Work
- 3 Proposed Approach
- 3.1 Pre-processing
- 3.2 Dataset Splitting, Balancing, and Hyper-parameter Tuning
- 3.3 Model Training, Validation, and Testing
- 4 Experimental Analaysis
- 4.1 Experimental Setup
- 4.2 Evaluation Metrics
- 4.3 Experimental Results
- 5 Conclusion
- References
- Correction to: Safeguarding Ecosystems and Efficiency in Peer-to-Peer File Sharing Systems: An IoT-Inspired Approach to Pollution Mitigation
- Author Index
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