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

• Record Nr.: UNISA996475763803316
• Pubbl/distr/stampa: Cham, Switzerland : , : Springer, , [2022]; ©2022
• ISBN: 3-031-07005-4
• Descrizione fisica: 1 online resource (406 pages)
• Collana: Communications in Computer and Information Science Ser. ; ; v.1576
• Disciplina: 621.367
• Soggetti: Image processing
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• 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.

Recent trends in image processing and pattern recognition : 5th International Conference, RTIP2R 2022, Kingsville, TX, USA, December 01-02, 2022, revised selected papers / / edited by K. C. Santosh, [and five others]

• Record Nr.: UNISA996547970503316
• Pubbl/distr/stampa: Cham, Switzerland : , : Springer, , [2023]; ©2023
• ISBN: 3-031-23599-1
• Edizione: [1st ed. 2023.]
• Descrizione fisica: 1 online resource (427 pages)
• Collana: Communications in Computer and Information Science, , 1865-0937 ; ; 1704
• Disciplina: 354.81150006
• Soggetti: Image processing
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Healthcare: medical imaging and informatics -- Data Characterization for Reliable AI in Medicine -- Alzheimer’s Disease Detection using Ensemble Learning and Artificial Neural Networks -- Semi-supervised Multi-domain Learning for Medical Image Classification -- Significant CC400 functional brain parcellations based LeNet5 Convolutional Neural Network for Autism Spectrum Disorder detection -- 2D respiratory sound analysis to detect lung abnormalities -- Analyzing Chest X-Ray to Detect the Evidence of Lung Abnormality due to Infectious Disease -- Chest X-ray Image Super-resolution via Deep Contrast Consistent Feature Network -- A Novel Approach to Enhance Effectiveness of Image Segmentation Techniques on Extremely Noisy ; Medical Images -- Federated Learning for Lung Sound Analysis -- Performance Analysis of CNN and Quantized CNN Model for Rheumatoid Arthritis Identification using Thermal Image -- Image Processing and Pattern Recognition of Micropores of Polysulfone Membrane for the Bio-separation of Viruses from Whole Blood -- An Extreme Learning Machine-basedAutoEncoder (ELM-AE)for denoising knee X-ray images and grading knee osteoarthritis severity -- Computer Vision and Pattern Recognition -- Motor Imagery Classification CombiningRiemannian Geometry and Artificial Neural Networks -- Autism Spectrum Disorder Detection using Transfer Learning with VGG 19, Inception V3 and DenseNet 201 -- Shrimp Shape Analysis by a Chord LengthFunction Based Methodology -- Supervised Neural Networks for Fruit Identification -- Targeted Clean-Label Poisoning Attacks On Federated Learning -- Building Marathi SentiWordNet -- A computational study on calibrated VGG19 formultimodal learning and representation insurveillance -- Automated Deep Learning based approach for Albinism Detection -- A Deep learning-based regression scheme for angle estimation in image dataset -- The classification of Native and Invasive Speciesin North America: A Transfer Learning and Random Forest Pipeline -- Internet of Things and Security -- Towards a Digital Twin Integrated DLT and IoT-based Automated Healthcare Ecosystem -- Enabling Edge Devices using Federated Learning and Big Data for Proactive Decisions -- IoT and Blockchain oriented gender determination of Bangladeshi populations -- Federated Learning based secured computational offloading in cyber-physical IoST systems -- A Hybrid Campus Security System Combined ofFace, Number-plate, and Voice Recognition -- Signal Processing and Machine -- Single-trial detection of event-related potentials with artificial examples based on coloring transformation -- Identifying the relationship between hypothesis and premise -- Data Poisoning Attack by Label Flipping onSplitFed Learning -- A Deep Learning-powered voice-enabled mathtutor for kids.
• Sommario/riassunto: This book constitutes the refereed proceedings of the 5th International Conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2022, held in Kingsville, TX, USA, in collaboration with the Applied AI Research Laboratory of the University of South Dakota, during December 01-02, 2022. The 31 full papers included in this book were carefully reviewed and selected from 69 submissions. They were organized in topical sections as follows: healthcare: medical imaging and informatics; computer vision and pattern recognition; internet of things and security; and signal processing and machine learning.

A visual history of the great civilizations / / Alberto Hernandez

• Record Nr.: UNINA9910158650503321
• Autore: Faulkner Nicholas
• Pubbl/distr/stampa: New York : , : Rosen Publishing, , 2017; �2017
• ISBN: 1-4994-6575-0
• Descrizione fisica: 1 online resource (100 pages) : color illustrations, maps
• Collana: A Visual History of the World
• Disciplina: 909
• Soggetti: Civilization - History
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Chronology -- Early Civilisations -- Classical Antiquity -- Civilisations of the Middle Ages.
• Sommario/riassunto: This book offers young readers a perspective into the some of the greatest civilizations in history. Readers will learn about early civilizations such as Mesopotamia and the kings of Israel, civilizations from classical antiquity such as dynastic China and the Persian empire, and civilizations of the Middle Ages, such as the Viking explorers and the Incas, to name a few.