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Recent Trends in Image Processing and Pattern Recognition : 6th International Conference, RTIP2R 2023, Derby, UK, December 7-8, 2023, Revised Selected Papers, Part II
| Recent Trends in Image Processing and Pattern Recognition : 6th International Conference, RTIP2R 2023, Derby, UK, December 7-8, 2023, Revised Selected Papers, Part II |
| Autore | Santosh K. C |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing AG, , 2024 |
| Descrizione fisica | 1 online resource (430 pages) |
| Altri autori (Persone) |
MakkarAaisha
ConwayMyra SinghAshutosh K VacavantAntoine Abou el KalamAnas BougueliaMohamed-Rafik HegadiRavindra |
| Collana | Communications in Computer and Information Science Series |
| ISBN | 3-031-53085-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Healthcare Informatics -- Leveraging Handwriting Impairment as a Biomarker for Early Parkinson's Disease Diagnosis -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Data Acquisition and Pre-processing -- 3.2 Data Augmentation -- 3.3 Model Definition and Training -- 4 Results and Discussion -- 5 Conclusion -- References -- Enhancing CT Image Visualization and Analysis Through Rescaling Raw Pixel Values to Hounsfield Units -- 1 Introduction -- 2 Hounsfield Unit -- 3 Hounsfield Unit Scaling -- 4 Results and Discussion -- 5 Conclusion -- References -- Diabetic Retinopathy Blood Vessel Detection Using Deep-CNN-Based Feature Extraction and Classification -- 1 Introduction -- 2 Methodology -- 2.1 Dataset Details -- 2.2 Pre-processing -- 2.3 Classification -- 3 Results and Discussion -- 3.1 Experimental Results -- 3.2 Results Comparison -- 4 Conclusion and Future Work -- References -- Detection of COVID-19 Disease Using Federated Learning -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Collection and Preprocessing -- 4 Experimental Results -- 5 Conclusion -- References -- Breast Cancer Detection Using Optimal Machine Learning Techniques: Uncovering the Most Effective Approach -- 1 Introduction -- 2 Literature Survey -- 3 Materials and Methodology -- 3.1 Data Preparation -- 3.2 About Dataset -- 3.3 Exploratory Data Analysis (EDA) -- 3.4 Feature Selection -- 3.5 Model Training and Evaluation -- 3.6 Model Comparison -- 4 Results, Conclusion, and Future Scope -- References -- Compressed Deep Learning Models with XAI for COVID-19 Detection Using CXR Images -- 1 Introduction -- 1.1 Motivation and Contribution -- 2 Related Work -- 3 Methodology -- 3.1 Preprocessing -- 3.2 Compression of Model -- 3.3 XAI -- 4 Results and Discussion -- 4.1 Dataset.
4.2 Experimental Results -- 5 Conclusion -- References -- HLB Disease Detection in Omani Lime Trees Using Hyperspectral Imaging Based Techniques -- 1 Introduction -- 2 Literature Review -- 2.1 Summary -- 3 Materials and Methods -- 3.1 Study Site -- 4 Proposed Methodology -- 4.1 Algorithm -- 4.2 Convolutional Neural Network (CNN) -- 5 Experimental Results and Analysis -- 5.1 Contributions -- 5.2 Delimitations -- 6 Conclusion -- References -- A Stack Ensemble Approach for Early Alzheimer Classification Using Machine Learning Algorithms -- 1 Introduction -- 2 Methodology -- 3 Materials and Methods -- 3.1 Logistic Regression -- 3.2 Random Forest -- 3.3 Naïve Bayes -- 3.4 Neural Network -- 3.5 Stack Ensemble -- 4 Performance Metrics -- 4.1 AUC -- 4.2 CA-Classification Accuracy -- 4.3 F1-Score -- 4.4 Precision -- 4.5 Recall -- 5 Results -- 5.1 Performance Curve - Lift Curve -- 5.2 Performance Curve - Cumulative Gains -- 5.3 Performance Curve - Precision-Recall -- 5.4 Confusion Matrix Interpretation -- 6 Conclusion -- References -- Analyzing Pulmonary Abnormality with Superpixel Based Graph Neural Network in Chest X-Ray -- 1 Introduction -- 2 Related Work - Graph Neural Networks -- 3 Methodology -- 3.1 Dataset -- 3.2 Data Preparation -- 3.3 Superpixel Graph -- 3.4 Network Models -- 4 Results and Discussions -- 5 Conclusion and Future Work -- References -- Silicosis Detection Using Extended Transfer Learning Model -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 3.1 Dataset -- 3.2 Methodology -- 4 Results -- 4.1 Transfer Learning Approach -- 4.2 Results of Proposed Approach -- 4.3 Disease Localization Using Grad-CAM Technique -- 4.4 Discussion -- 5 Conclusion -- References -- Automated Make and Model Identification of Reverse Shoulder Implants Using Deep Learning Methodology -- 1 Introduction -- 2 Literature Review. 3 Dataset Description -- 4 Methods and Methodology -- 4.1 Proposed Approach -- 4.2 Training Set -- 4.3 Testing Set -- 4.4 Data Augmentation -- 4.5 Deep Learning Methods -- 4.6 Proposed Approach -- 4.7 Performance Metrics -- 5 Results and Discussion -- 5.1 Data Augmentation -- 5.2 Deep Learning Results -- 6 Conclusion -- References -- COVID-19 Disease Prediction Using Generative Adversarial Networks with Convolutional Neural Network (GANs-CNN) Model -- 1 Introduction -- 2 Literature Review -- 3 Experimental Setup -- 3.1 CNN Model -- 3.2 GANs Model -- 3.3 Image Smoothing Technique -- 3.4 Proposed System Model -- 3.5 Evaluation -- 4 Results and Discussion -- 5 Conclusion -- References -- Modified Snapshot Ensemble Algorithm for Skin Lesion Classification -- 1 Introduction -- 1.1 Contributions -- 2 Methodology -- 2.1 Preprocessing -- 2.2 Snapshot Ensemble Technique -- 3 Proposed Algorithm -- 3.1 Model Creation -- 3.2 Modified Snapshot Ensemble -- 4 Experimental Results -- 4.1 Dataset Details -- 4.2 Model Training and Testing -- 4.3 Snapshot Ensemble Calculation -- 4.4 Comparison and Discussion -- 5 Conclusion -- References -- A Residual Learning Approach Towards the Diagnosis of Colorectal Disease Effectively -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Overview -- 3.2 Preprocessing -- 3.3 Proposed Methodology -- 3.4 Proposed Method Architecture -- 4 Experimental Results and Analysis -- 4.1 Dataset -- 4.2 Comparison with the Benchmark Results -- 5 Conclusion -- References -- Realistic Skin Image Data Generation Leveraging Conditional GAN and Classification Using Deep CNN -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 Loss Functions -- 4 Results and Discussions -- 5 Conclusion -- References -- Radiography and Thermography Based Image Processing Techniques for Assessment of Lower Back Pain -- 1 Introduction. 2 Earlier Work -- 3 Methodology -- 3.1 X-Ray Image Processing -- 3.2 Thermal Image Processing -- 4 Results -- 4.1 X-Ray Based Image Analysis -- 4.2 Thermal Image Analysis -- 5 Conclusion -- References -- Exploring Imaging Biomarkers for Early Detection of Alzheimer's Disease Using Deep Learning: A Comprehensive Analysis -- 1 Introduction -- 2 Background Research -- 3 Retina Scan in Detection of Alzheimer -- 4 Role of Deep Learning -- 4.1 Emerging DL Technologies in AD Research -- 5 Conclusion -- References -- Pattern Recognition in Blockchain, Cyber and Network Security, and Cryptography -- VAIDS: A Hybrid Deep Learning Model to Detect Intrusions in MQTT Protocol Enabled Networks -- 1 Introduction -- 1.1 MQTT Network Infrastructure Overview -- 1.2 MQTT Packet Structure -- 1.3 Network Attacks on IoT Infrastructure -- 2 Related Work -- 3 Dataset -- 3.1 Dataset Description -- 3.2 Dataset Labeling -- 4 Proposed Model -- 5 Experiments -- 6 Evaluation Metrics -- 7 Results -- 8 Conclusion and Future Scope -- References -- Crypto Bank: Cryptocurrency Wallet Based on Blockchain -- 1 Introduction -- 1.1 The Idea of Cryptocurrencies - the 1980s -- 1.2 The Launch of Bitcoin - 2008 -- 1.3 The Initial Crypto Market Development -- 1.4 The Rise of the Crypto Bank -- 1.5 Crypto Wallets -- 2 Literature Review -- 2.1 Bitcoin, the First Cryptocurrency -- 2.2 Ethereum and Smart Contracts -- 2.3 The Token Economy -- 3 Background Details -- 4 Proposed Work -- 5 Methodology -- 6 Comparative Analysis -- 7 Conclusion and Future Scope -- References -- Large-Language-Models (LLM)-Based AI Chatbots: Architecture, In-Depth Analysis and Their Performance Evaluation -- 1 Introduction -- 2 Literature Review -- 3 Identified Issues and Challenges -- 4 Problem Statement -- 5 Contributions -- 6 Methodology -- 6.1 GPT-3 -- 6.2 GPT-4 -- 6.3 AutoGPT -- 6.4 LLaMA -- 6.5 Vicuna -- 6.6 Alpaca. 6.7 BARD -- 7 Results, Analysis, and Discussion -- References -- CincoCrypto - A Cryptocurrency Price Forecasting Tool for Everyone -- 1 Introduction -- 1.1 Research Contributions -- 1.2 Limitations -- 2 Literature Review -- 3 Methodology -- 3.1 Datasets -- 3.2 Proposed Work -- 4 Results -- 5 Conclusion -- 6 Future Work -- References -- Deep Neural Networks Based Security Solution for ATM Transactions -- 1 Introduction -- 2 Related Work -- 3 Proposed Model -- 4 Conclusion and Future Work -- References -- A Comprehensive Analysis of Blockchain Network Security: Attacks and Their Countermeasures -- 1 Introduction -- 1.1 Characteristics of Blockchain -- 1.2 Applications of Blockchain -- 2 Blockchain Security -- 2.1 Blockchain Attacks -- 3 Summary of Blockchain Attacks -- 4 Conclusion -- References -- Enhancing Android Malware Detection: CFS Based Texture Feature Selection and Ensembled Classifier for Malware App Analysis -- 1 Introduction and Motivation -- 1.1 Introduction -- 1.2 Motivation -- 2 Background -- 2.1 Introduction to Android -- 2.2 Android Malware -- 2.3 Android Malware Detection -- 2.4 Machine Learning -- 3 Related Work -- 4 Methodology -- 4.1 Image Formation -- 4.2 Feature Extraction -- 4.3 Feature Filtration -- 4.4 Classification Algorithms -- 5 Experimental Setup -- 5.1 Dataset -- 6 Results and Discussion -- 6.1 Image Conversion -- 6.2 Feature Extraction -- 6.3 Feature Filtration -- 6.4 Classification Results on Features Collected from Various Texture Feature Extraction Methods -- 6.5 Comparison with Previous Techniques -- 7 Conclusion and Future Scope -- References -- Blockchain-Enhanced Federated Learning for Secure Malicious Activity Detection in Cyber-Physical Systems -- 1 Introduction -- 2 Related Work -- 2.1 Feature Selection Techniques -- 2.2 Machine Learning-Based Approaches -- 2.3 Blockchain-Based Security. 3 System Architecture. |
| Record Nr. | UNINA-9910806192403321 |
Santosh K. C
|
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| Cham : , : Springer International Publishing AG, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Recent Trends in Image Processing and Pattern Recognition : 6th International Conference, RTIP2R 2023, Derby, UK, December 7-8, 2023, Revised Selected Papers, Part I
| Recent Trends in Image Processing and Pattern Recognition : 6th International Conference, RTIP2R 2023, Derby, UK, December 7-8, 2023, Revised Selected Papers, Part I |
| Autore | Santosh K. C |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing AG, , 2024 |
| Descrizione fisica | 1 online resource (421 pages) |
| Altri autori (Persone) |
MakkarAaisha
ConwayMyra SinghAshutosh K VacavantAntoine Abou el KalamAnas BougueliaMohamed-Rafik HegadiRavindra |
| Collana | Communications in Computer and Information Science Series |
| ISBN | 3-031-53082-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Artificial Intelligence and Applied Machine Learning -- Building a Heroin Abuse Prediction Model: A Generalized Machine Learning Approach -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset Details -- 2.2 Data Preprocessing -- 2.3 Performance Evaluation Metrics -- 2.4 Methods Used -- 2.5 Feature Importance -- 3 Results -- 3.1 Result of Exploratory Data Analysis (EDA) -- 3.2 Result of Machine Learning Analysis -- 4 Discussion -- References -- Fake News Detection Using Transfer Learning -- 1 Introduction -- 2 Problem Statement -- 3 Methodology -- 3.1 ULMFiT (Universal Language Model Fine-tuning) -- 4 Experimental Setup -- 4.1 Fake News Dataset Pre-processing -- 5 Results -- 6 Conclusion -- References -- Deep Learning Envisioned Accident Detection System -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Phase 1 - Vehicle Detection -- 3.2 Phase 2 - Vehicle Tracking -- 3.3 Phase 3 - Accident Classification -- 4 Results -- 4.1 AUC-ROC Analysis -- 5 Conclusion -- References -- Revolutionizing Drug Discovery: Unleashing AI's Potential in Pharmaceutical Innovation -- 1 Introduction -- 2 Overview of Technology -- 3 Enabling Technology -- 3.1 AI in Drug Design (DD) -- 3.2 AI in Poly-Pharmacology (PP) -- 3.3 AI in Drug Repurposing (DR) -- 3.4 AI in Drug Screening (DS) -- 4 Result -- 5 Limitation -- 6 Conclusion and Future Scope -- References -- Empathy-Driven Chatbots for the Arabic Language: A Transformer Based Approach -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Data Collecting and Translating -- 3.2 Data Cleaning and Processing -- 3.3 Word-Vector Dictionary (Embedding Matrix) -- 3.4 Model Evaluation -- 4 Experiments -- 4.1 Hyperparameters -- 4.2 Experimental Environment -- 4.3 Pre-training -- 4.4 Fine-Tuning -- 5 Discussion.
6 Conclusion -- References -- Image Classification Using Federated Learning -- 1 Introduction -- 2 Review of Literature -- 3 Proposed Methods -- 3.1 Objective -- 4 Proposed Dataset -- 5 Experimental Set and Result Analysis -- 5.1 Implementation Detail -- 5.2 Result Analysis -- 6 Conclusion -- References -- Preserving Accuracy in Federated Learning via Equitable Model and Efficient Aggregation -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data -- 3.2 Creating Decentralized Datasets -- 3.3 Structure of Neural Networks -- 3.4 Aggregation Model -- 3.5 Equitably Updating the Clients -- 3.6 Comparator Algorithm -- 4 Experimental Evaluations -- 4.1 IID Partitioning and Evaluation -- 4.2 Non-IID Partitioning and Evaluation -- 4.3 Applying Equitable Model -- 5 Conclusion -- References -- Fake News Investigation Using Ensemble Machine Learning Techniques -- 1 Introduction -- 1.1 Novelty -- 1.2 Motivation -- 1.3 Background Knowledge -- 2 Proposed Methodology -- 2.1 Problem Statement Modelling and Research Contributions -- 2.2 Methodology -- 2.3 Logistic Regression -- 2.4 Decision Tree Classification -- 2.5 Random Forest Classification -- 2.6 Gradient Boost Classification -- 3 Experimental Setup and Result Analysis -- 3.1 Dataset Discription -- 3.2 Pre-processing -- 3.3 Results -- 3.4 Conclusion -- 3.5 Future Scope -- References -- Deep Learning Based Bug Detection in Solidity Smart Contracts -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Bug Injection Technique -- 3.2 Data Pre-processing Pipeline -- 3.3 Network Architecture -- 4 Results -- 5 Conclusion -- References -- Comparative Analysis of CNN Pre-trained Model for Stock Market Trend Prediction -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Model Architecture -- 3.2 CNN Architecture -- 3.3 Labeling of Stock's Close-Price -- 3.4 Image Generation. 4 Results -- 4.1 Dataset and Evaluation Criterion -- 4.2 Experimentation with Different Pretrained Model -- 5 Conclusion -- References -- Deep Reinforcement Learning Based Energy-Efficient Design for STAR-IRS Assisted V2V Users -- 1 Introduction -- 1.1 Related Work -- 1.2 Motivation and Contribution -- 1.3 Organization -- 2 System Model and Problem Formulation -- 2.1 System Model -- 2.2 Channel Model -- 2.3 Energy Efficiency Evaluation -- 2.4 Problem Formulation -- 3 Proposed Scheme -- 3.1 Markov Decision Process Model -- 3.2 Environment -- 3.3 Agent -- 3.4 State Space -- 3.5 Action Space -- 3.6 Reward -- 4 Performance Evaluation -- 4.1 Simulation Parameters -- 4.2 Results and Discussion -- 5 Conclusion -- References -- Deep Reinforcement Learning Based Intelligent Resource Allocation Techniques with Applications to Cloud Computing -- 1 Introduction -- 2 Related Work -- 3 Conclusion -- References -- A Review on Machine Learning Techniques in IoT-Based Smart Grid Applications -- 1 Introduction -- 2 Applications of Machine Learning in Modern Power Grids -- 3 Cyber Security in Modern Power Grids -- 4 Findings -- 5 Discussion -- 6 Conclusion -- References -- Transformation of Corporate Social Responsibility Practices: Adapting Artificial Intelligence and Internet of Things -- 1 Introduction -- 2 Overview of Adaptation of AI and IoT in CSR -- 3 Enabling Technologies -- 3.1 Artificial Intelligence (AI) -- 3.2 Internet of Things (IoT) -- 3.3 Blockchain -- 4 Array of Challenges Using AI and IoT in Transformation CSR -- 5 Recommendations -- 6 Conclusion -- References -- Various Active Learning Strategies Analysis in Image Labeling: Maximizing Performance with Minimum Labeled Data -- 1 Introduction -- 1.1 Background and Motivation -- 1.2 Hypothesis -- 1.3 Objective and Contribution -- 2 Problem Statement -- 3 Literature Review -- 4 Proposed Methodology. 4.1 Dataset Description -- 4.2 Processing -- 4.3 Approaches Used -- 5 Results -- 6 Conclusion -- 7 Future Work -- References -- Applied Image Processing and Pattern Recognition -- Potato Leaf Disease Classification Using Federated Learning -- 1 Introduction -- 2 Related Work -- 3 Federated Learning (FL) -- 4 Dataset -- 5 Experiment Results -- 6 Conclusion and Discussion -- References -- Sugarcane Bud Detection Using YOLOv5 -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Methods -- 3.2 YOLOv5 Architecture -- 4 Results -- 5 Conclusion -- 5.1 Future Works -- References -- ELA-Conv: Forgery Detection in Digital Images Based on ELA and CNN -- 1 Introduction -- 1.1 Active Approaches -- 1.2 Passive Approaches -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Image Preprocessing -- 3.2 Error Level Analysis -- 3.3 CNN Architectures -- 3.4 Dataset Description -- 3.5 Proposed System -- 3.6 Model Training -- 4 Results and Discussion -- 4.1 Evaluation Metrics -- 4.2 Results -- 5 Conclusion and Future Scope -- References -- Leveraging Wavelets and Deep CNN for Sleep Pattern Recognition in Road Safety: An EEG Study -- 1 Introduction -- 2 Methodology -- 2.1 Data Acquisition -- 2.2 Data Preprocessing -- 2.3 Continuous Wavelet Transform -- 2.4 Dataset Generation -- 2.5 Data Preparation and Transfer Learning -- 2.6 Performance Assessment Metrics -- 3 Results and Discussion -- 4 Conclusions -- References -- Recognition and Transcription of Archaic Handwritten Modi Script Document: A Thought-Provoking Crucial Research Area -- 1 Introduction -- 2 Modi Script Datasets -- 3 Modi Script Document Preprocessing Methodologies -- 3.1 Degradation Detection and Removal -- 3.2 Skew Detection and Correction -- 4 Modi Script Document Segmentation Methodologies -- 4.1 Text Line Segmentation -- 4.2 Character Segmentation. 5 Modi Script Alphabet Recognition Methodologies -- 6 Future Directions -- 7 Conclusion -- References -- An Arabic Chatbot Leveraging Encoder-Decoder Architecture Enhanced with BERT -- 1 Introduction -- 2 Related Works -- 2.1 English Chatbots -- 2.2 Arabic Chatbot -- 3 Proposed Model -- 3.1 Data Collection and Preprocessing -- 3.2 Proposed Model -- 4 Experiments Results -- 5 Conclusion -- References -- FNMD: An Evaluation of Machine Learning and Deep Learning Techniques for Fake News Detection -- 1 Introduction -- 2 Literature -- 3 Research Methodology -- 3.1 Data Set -- 3.2 The Implementation Process -- 4 Experimental Results and Discussion -- 4.1 Input Features -- 4.2 Analysis of Results -- 4.3 Discussion -- 5 Implications -- 6 Limitations -- 7 Conclusions and Future Work -- References -- Enhancing Robotic Systems for Revolutionizing Healthcare Using Markov Decision Processes -- 1 Introduction -- 2 Recent Related Work -- 2.1 Reinforcement Learning for Healthcare Robotics -- 2.2 Application of MDPs in Specific Healthcare Domains -- 2.3 Human-Robot Collaboration Using MDPs -- 2.4 Incorporation of Uncertainty Modeling Techniques -- 2.5 Ethical Considerations in Healthcare Robotics and MDPs -- 3 MDPs and Their Variants -- 3.1 Completely Observable MDP (COMDP) -- 3.2 Partially Observable MDP -- 4 COMDP in Robotics -- 5 POMDP in Robotics -- 6 Human-Robot Interaction -- 6.1 Types of Interaction -- 6.2 Understanding Human Intentions Using MDPs -- 7 Ethical and Privacy Considerations in Healthcare Robotics -- 8 Conclusion -- References -- Optimizing Drone Navigation Using Shortest Path Algorithms -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Haversine Method -- 3.2 Dijkstra's Algorithm -- 3.3 Travelling Salesman Problem Algorithm -- 4 Results and Discussion -- 5 Conclusion -- References. Trees Detection from Aerial Images Using the YOLOv5 Family. |
| Record Nr. | UNINA-9910831003403321 |
|
Santosh K. C
|
||
| Cham : , : Springer International Publishing AG, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||