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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
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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 : 4th International Conference, RTIP2R 2021, Msida, Malta, December 8-10, 2021, revised selected papers / / edited by K. C. Santosh, Ravindra Hegadi, Umapada Pal
| Recent trends in image processing and pattern recognition : 4th International Conference, RTIP2R 2021, Msida, Malta, December 8-10, 2021, revised selected papers / / edited by K. C. Santosh, Ravindra Hegadi, Umapada Pal |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (406 pages) |
| Disciplina | 621.367 |
| Collana | Communications in Computer and Information Science Ser. |
| Soggetto topico | Image processing |
| ISBN | 3-031-07005-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Healthcare: Medical Imaging and Informatics -- Cleaning Highly Unbalanced Multisource Image Dataset for Quality Control in Cervical Precancer Screening -- 1 Introduction -- 2 Image Data -- 3 Method -- 4 Experiments and Discussions -- 5 Conclusion and Future Work -- References -- Detection of Male Fertility Using AI-Driven Tools -- 1 Introduction -- 2 Related Works -- 3 Methods -- 3.1 Features Detailing -- 3.2 Feature Selection -- 3.3 Feature Selection -- 3.4 The Workflow of Proposed Model -- 4 Experiments -- 4.1 Data -- 4.2 Evaluation Protocols -- 4.3 Results -- 5 Conclusion -- References -- An Empirical Study of Vision Transformers for Cervical Precancer Detection -- 1 Introduction -- 2 Related Work -- 3 Experiments -- 3.1 Data Preparation -- 3.2 Architecture -- 3.3 Training Setup -- 4 Results and Discussions -- 5 Conclusion and Future Work -- References -- CheXNet for the Evidence of Covid-19 Using 2.3K Positive Chest X-rays -- 1 Introduction -- 2 Chest X-ray Dataset -- 3 CheXNet and Implementation -- 4 Experimental Results -- 4.1 Evaluation Protocol and Performance Metrics -- 4.2 Results Analysis -- 4.3 Comparative Study -- 5 Conclusion and Future Work -- References -- An Enhanced Deep Convolution Neural Network Model to Diagnose Alzheimer's Disease Using Brain Magnetic Resonance Imaging -- 1 Introduction -- 2 Proposed Methodology -- 2.1 Data Pre-processing -- 2.2 Deep CNN: Architecture and Implementation -- 2.3 Hyper Parameters in Deep CNN -- 3 Experiments -- 3.1 Dataset -- 3.2 Validation Protocol and Evaluation Metrics -- 3.3 Results and Discussion -- 4 Conclusion -- References -- Automatic Knee Osteoarthritis Stages Identification -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Acquisition -- 3.2 Left and Right Knee Segmentation -- 3.3 ROI Detection.
3.4 DNN-Based Classification System -- 4 Experimental Setup and Result Discussion -- 4.1 Comparison of OACnet with Other DNN-Based Models -- 5 Conclusion -- References -- Stacked Dark COVID-Net: A Multi-class Multi-label Classification Approach for Diagnosing COVID-19 Using Chest X-Ray Images -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Image Processing -- 3.2 Layered DarkNet (LDN) -- 3.3 Novel Stacked Dark COVID-Net -- 4 Experimental Setup and Discussions -- 4.1 Experimental Setup -- 4.2 Dataset Description -- 5 Conclusions -- References -- Image Augmentation for Improving Automated Eligibility-Classification for Cervical Precancer Ablation Treatment -- 1 Introduction -- 2 Methods -- 2.1 Dataset and Annotation -- 2.2 CycleGan -- 2.3 Customized CNN -- 3 Experiments -- 3.1 Augmented Images -- 3.2 Treatability Classification Performance -- 3.3 Comparing the Visualization -- 4 Conclusion -- References -- Osteoarthritis Detection Using Densely Connected Neural Network -- 1 Introduction -- 2 Related Work -- 3 Architecture of Dense Net -- 4 Design of OA Detection and Classification Model -- 4.1 Input Image Acquisition -- 4.2 Pre-processing -- 4.3 Feature Extraction -- 4.4 Image Classification -- 5 Results and Discussion -- 6 Conclusion -- References -- Generic Foreign Object Detection in Chest X-rays -- 1 Introduction -- 2 Related Works -- 3 YOLOv4, Architecture and Implementation -- 4 Experiments -- 4.1 Dataset -- 4.2 Results and Analysis -- 5 Conclusions -- References -- Mammogram Mass Classification: A CNN-Based Technique Applied to Different Age Groups -- 1 Contribution Outline -- 1.1 Traditional Classifiers -- 1.2 CNN Architecture -- 2 Experiments -- 2.1 Dataset and Pre-processing -- 2.2 Age Grouping -- 2.3 Evaluation Metrics -- 2.4 Evaluation Strategy and System Configuration -- 2.5 Results and Analysis. 2.6 Comparative Analysis with Previous Relevant Work -- 3 Conclusions and Future Work -- References -- Computer Vision and Pattern Recognition -- Complex Object Detection Using Light-Field Plenoptic Camera -- 1 Introduction -- 2 Plenoptic Camera Calibration -- 3 Methods -- 3.1 Feature Detection -- 3.2 Feature Matching -- 3.3 Transform Model Estimation -- 3.4 Results -- 3.5 Conclusions -- References -- Real-Time Face Recognition for Organisational Attendance Systems -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 4 Experimental Results and Discussion -- 5 Conclusion -- References -- Harnessing Sustainable Development in Image Recognition Through No-Code AI Applications: A Comparative Analysis -- 1 Introduction -- 2 Literature Review -- 2.1 Previous Research -- 3 Methodology -- 3.1 Dataset -- 3.2 Hardware -- 3.3 Software -- 3.4 ResNet - 50 V2 -- 3.5 MobileNetV2 -- 4 Results -- 5 Discussion -- References -- Evaluating Performance of Adam Optimization by Proposing Energy Index -- 1 Introduction -- 2 Related Work -- 2.1 AdaGrad -- 2.2 AdaDelta -- 2.3 RMSProp -- 2.4 Adam -- 2.5 Energy Index Based Optimization Method (EIOM) -- 3 Introducing EI to Adam -- 4 Experiments and Analysis -- 4.1 Logistic Regression -- 4.2 Support Vector Machine -- 5 Conclusion and Future Direction -- References -- An Alignment-Free Fingerprint Template Protection Technique Based on Minutiae Triplets -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Technique -- 3.1 Non-invertible Feature Extraction -- 3.2 Secured Template Generation -- 3.3 Security Enhancement of the Generated Template -- 3.4 Matching -- 4 Experimental Analysis -- 4.1 Revocability -- 4.2 Diversity -- 4.3 Security -- 4.4 Performance -- 5 Conclusion -- References -- Early Prediction of Complex Business Processes Using Association Rule Based Mining -- 1 Introduction -- 2 Related Work. 3 Association Rule Mining -- 4 The CBA-Based Prediction Model -- 5 Experimental Results -- 5.1 Comparative Analysis -- 6 Conclusion -- References -- A Framework for Masked-Image Recognition System in COVID-19 Era -- 1 Introduction -- 1.1 Objectives -- 2 Literature Review -- 3 Problem Formulation -- 4 Proposed Solutions -- 4.1 Programming Languages and Tools -- 4.2 Web Application Frameworks -- 4.3 Computer Vision Frameworks -- 4.4 Algorithms -- 4.5 Approaches -- 5 Specification and Design -- 5.1 System Requirements -- 5.2 Principle System Components and Requirements -- 6 Implementations and Result Analysis -- 6.1 Home Component -- 6.2 Camera Component -- 6.3 Login Component -- 6.4 Profile Component -- 6.5 Results Analysis -- 7 Conclusions and Future Work -- References -- A Deep-Learning Based Automated COVID-19 Physical Distance Measurement System Using Surveillance Video -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Human Detection -- 3.2 Human Tracking -- 3.3 Distance Measurement -- 4 Experimental Results and Discussions -- 4.1 Dataset and Training Details -- 4.2 Results and Discussions -- 5 Conclusion -- References -- Face Mask Detection Using Deep Hybrid Network Architectures -- 1 Introduction and Problem Understanding -- 2 Related Works -- 3 Dataset and Data Preprocessing -- 3.1 Data Description -- 3.2 Resizing -- 4 Description of the Network Architectures and Machine Learning Algorithms -- 4.1 ResNet50 -- 4.2 VGG16 -- 4.3 Support Vector Machines -- 4.4 GBDecision Trees -- 4.5 Neural Networks -- 4.6 Hybrid Models -- 5 Proposed Model: ResNet50 + SVM -- 6 Results and Discussion -- 7 Conclusion -- References -- A Super Feature Transform for Small-Size Image Forgery Detection -- 1 Introduction -- 2 Related Works and Problem Context -- 2.1 Preliminaries of Super Resolution Algorithms -- 2.2 Review of Forgery Detection Algorithms. 3 Proposed Detection Model -- 3.1 Super Feature Transform (SFT) -- 3.2 Feature Filtering and Forged Region Localization -- 4 Experimentation and Analysis -- 4.1 Evaluation of Super Feature Transform -- 4.2 Detection Results with Post-processing Actions -- 5 Conclusion -- References -- Document Analysis and Recognition -- UHTelHwCC: A Dataset for Telugu Off-line Handwritten Character Recognition -- 1 Introduction -- 2 Related Work -- 3 UHTelHwCC Creation -- 4 UHTelHwCC Characteristics -- 4.1 Sample Distribution -- 4.2 Data Splits -- 4.3 Writers Details -- 5 Experiments -- 6 Conclusion -- References -- Inflectional and Derivational Hybrid Stemmer for Sentiment Analysis: A Case Study with Marathi Tweets -- 1 Introduction -- 2 Related Work -- 3 Marathi Morphology -- 4 Marathi Stemming Algorithm -- 4.1 Data Collection -- 4.2 Cleaning -- 4.3 Stop Word Removal -- 4.4 Marathi Subjective Lexicon (Adjective-Adverb) -- 4.5 Stemming -- 5 Experiments and Results -- 5.1 Performance of the Stemmer -- 5.2 Tweet Classification and Stemmer Validation -- 5.3 Comparison with Existing Marathi Stemmers -- 6 Conclusion -- References -- Adaptive Threshold-Based Database Preparation Method for Handwritten Image Classification -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Deep Neural Network -- 3.2 Feature Extraction with Adaptive Threshold -- 3.3 Classification and Recognition -- 4 Experimental Setup and Evaluation Protocol -- 4.1 Dataset and Pre-processing -- 4.2 Evolution Protocol -- 5 Conclusion and Future Scope -- References -- A Graph-Based Holistic Recognition of Handwritten Devanagari Words: An Approach Based on Spectral Graph Embedding -- 1 Introduction -- 2 Proposed Model -- 2.1 Pre-processing -- 2.2 Proposed Graph Extraction/Representation -- 2.3 Edge Connecting, Labelling and Selection of Graph Associated Matrices. 2.4 Spectral Decomposition of Word Graph Associated Matrices. |
| Record Nr. | UNISA-996475763803316 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Recent Trends in Image Processing and Pattern Recognition : 4th International Conference, RTIP2R 2021, Msida, Malta, December 8-10, 2021, Revised Selected Papers / / edited by KC Santosh, Ravindra Hegadi, Umapada Pal
| Recent Trends in Image Processing and Pattern Recognition : 4th International Conference, RTIP2R 2021, Msida, Malta, December 8-10, 2021, Revised Selected Papers / / edited by KC Santosh, Ravindra Hegadi, Umapada Pal |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (406 pages) |
| Disciplina | 621.367 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Artificial intelligence Computer engineering Computer networks Social sciences - Data processing Education - Data processing Data protection Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence Computer Engineering and Networks Computer Application in Social and Behavioral Sciences Computers and Education Data and Information Security |
| ISBN | 3-031-07005-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Healthcare: medical imaging and informatics -- Computer Vision and Pattern Recognition -- Document analysis and recognition -- Signal processing and machine learning -- Satellite imaging and remote sensing. |
| Record Nr. | UNINA-9910574074603321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||