Count Taaffe's letters from the imperial camp, to his brother the Earl of Carlingford here in London [[electronic resource] ] : giving an account of the most considerable actions, both before, and at, the raising of the siege at Vienna, together with several remarkable passages afterward, in the late victorious campagne against the Turks in Hungary : with an addition of two other letters from a young English nobleman, a voluntier in the imperial army

• Record Nr.: UNISA996389350803316
• Autore: Carlingford Francis Taaffe, Earl of, <1639-1704.>
• Pubbl/distr/stampa: London, : Printed for T.B. and are to be sold by Roberrt Clavel at the Peacock in St. Pauls Church-yard, 1684
• Descrizione fisica: [4], 34 p
• Altri autori (Persone): CarlingfordNicholas Taaffe, Earl of, -1690
• Soggetti: Turks - Hungary; Vienna (Austria) History Siege, 1683
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Reproduction of original in: Durham University Library.
• Sommario/riassunto: eebo-0044

Computer Analysis of Images and Patterns : 20th International Conference, CAIP 2023, Limassol, Cyprus, September 25-28, 2023, Proceedings, Part II

• Record Nr.: UNISA996550554403316
• Autore: Tsapatsoulis Nicolas
• Pubbl/distr/stampa: Cham : , : Springer, , 2023; ©2023
• ISBN: 3-031-44240-7
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (295 pages)
• Collana: Lecture Notes in Computer Science Series ; ; v.14185
• Altri autori (Persone): LanitisAndreas; PattichisMarios; PattichisConstantinos; KyrkouChristos; KyriacouEfthyvoulos; TheodosiouZenonas; PanayidesAndreas
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Intro -- Preface -- Organization -- Keynote Lectures -- Semiconductor Chips in the Center of Geopolitical Competition -- Improving Contour Detection by Surround Suppression of Texture -- Contents - Part II -- Contents - Part I -- Biometrics - Human Pose Estimation - Action Recognition -- A Systematic Approach for Automated Lecture Style Evaluation Using Biometric Features -- 1 Introduction -- 2 Literature Review -- 3 Defining a Good Lecture Style Profile -- 4 Lecture Style Quality Score Estimation. -- 4.1 Facial Expressions -- 4.2 Activity Detection -- 4.3 Speech Recognition -- 4.4 Hand Movement -- 4.5 Facial Pose Estimation -- 4.6 Merging Metrics -- 5 Evaluation -- 6 Conclusions -- References -- Highly Crowd Detection and Counting Based on Curriculum Learning -- 1 Introduction -- 2 Proposed Approach -- 3 Dataset -- 4 Experimental Results -- 5 Conclusion -- References -- Race Bias Analysis of Bona Fide Errors in Face Anti-spoofing -- 1 Introduction -- 2 Background -- 2.1 Face Anti-spoofing ; -- 2.2 Bias in Machine Learning -- 3 Experimental Setup -- 3.1 The VQ-VAE Classifier -- 3.2 Overview of the Bias Analysis Process -- 4 Bias Analysis on SiW -- 4.1 Statistical Analysis of the Binary Outcomes -- 4.2 Statistical Analysis of the Scalar Responses -- 5 Bias Analysis on RFW -- 6 Conclusion -- References -- Fall Detection with Event-Based Data: A Case Study -- 1 Introduction -- 2 Related Works -- 3 Methods -- 3.1 The Data Set -- 3.2 Fall Detection Approach -- 4 Experimental Results -- 5 Discussion and Conclusion -- References -- Towards Accurate and Efficient Sleep Period Detection Using Wearable Devices -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Dataset -- 3.2 Problem Modelling -- 4 Models -- 5 Evaluation and Results -- 5.1 Baseline Study -- 5.2 Machine Learning and Deep Learning Models -- 6 Clinical Results -- 7 Conclusion and Future Work.; References -- RLSTM: A Novel Residual and Recurrent Network for Pedestrian Action Classification -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Spatio-Temporal RLSTM -- 3.2 MapGrad Layer -- 4 Experimental Results -- 4.1 Dataset -- 4.2 Ablation Study -- 4.3 Comparison with the State-of-the-Art -- 5 Conclusions and Future Work -- References -- Biomedical Image and Pattern Analysis -- Temporal Sequences of EEG Covariance Matrices for Automated Sleep Stage Scoring with Attention Mechanisms -- 1 Introduction -- 2 State of the Art -- 3 Method -- 3.1 From EEG Signals to Covariance-Derived SPD Matrices -- 3.2 The Model -- 4 Experiments -- 4.1 Dataset Used -- 4.2 Model Validation -- 4.3 Reproducing the State of the Art -- 4.4 Analysis of Results -- 5 Conclusion -- References -- A Complete AI-Based System for Dietary Assessment and Personalized Insulin Adjustment in Type 1 Diabetes Self-management -- 1 Introduction -- 2 Related Work -- 2.1 Computer Vision in Dietary Assessment -- 2.2 Reinforcement Learning in Blood Glucose Control -- 3 Methodology -- 3.1 System Outline -- 3.2 Computer Vision Module -- 3.3 Reinforcement Learning Module -- 4 Experimental Setup -- 4.1 Food-Related Datasets -- 4.2 In Silico Environment -- 4.3 Scenario -- 5 Results -- 5.1 Complete System -- 5.2 Computer Vision Module -- 6 Conclusion -- References -- COFI - Coarse-Semantic to Fine-Instance Unsupervised Mitochondria Segmentation in EM -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Dataset Description and Annotation -- 3.2 Coarse Semantic Segmentation -- 3.3 Fine Instance Segmentation -- 4 Experiments and Results -- 5 Discussion and Conclusion -- References -- Empirical Study of Attention-Based Models for Automatic Classification of Gastrointestinal Endoscopy Images -- 1 Introduction -- 2 Attention-Based Models -- 2.1 MobileViT Family -- 2.2 CoAtNet -- 2.3 CMT.; 2.4 DaViT -- 3 Dataset and Metrics -- 3.1 Hyper-Kvasir Dataset -- 3.2 Performance Metrics -- 4 Experiments and Results -- 4.1 Implementation Details -- 4.2 Comparison of Architectures -- 4.3 Influence of the Green Patches -- 4.4 Comparison to the State of the Art -- 5 Conclusions and Future Work -- References -- Classification of Breast Micro-calcifications as Benign or Malignant Using Subtraction of Temporally Sequential Digital Mammograms and Machine Learning -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data Collection and Description -- 2.2 MCs Detection and Segmentation -- 2.3 Feature Extraction and Selection -- 2.4 Training and Comparison of Classifier Designs -- 3 Experimental Results -- 4 Discussion -- 5 Conclusion -- References -- Fourier Descriptor Loss and Polar Coordinate Transformation for Pericardium Segmentation -- 1 Introduction -- 1.1 Related Work -- 1.2 Contribution -- 2 Methodology -- 3 Experiments -- 3.1 Data -- 3.2 Implementation Details -- 3.3 Results -- 4 Conclusions and Future Work -- References -- Stroke Risk Stratification ; Using Transfer Learning on Carotid Ultrasound Images -- 1 Introduction -- 1.1 Artificial Intelligence-Based Stroke Risk Assessment -- 2 Materials and Methods -- 2.1 Carotid Ultrasound Images and Patient Data -- 2.2 Image Preprocessing -- 2.3 Transfer Learning Models -- 2.4 Model Training Process -- 2.5 Model Carotid Plaque Classification Performance -- 2.6 Saliency Maps Per Carotid Plaque Category -- 3 Results -- 4 Discussion -- References -- A Comparative Study of Explainable AI models in the Assessment of Multiple Sclerosis -- 1 Introduction -- 2 Materials -- 3 Methods -- 3.1 Learning Method A -- 3.2 Learning Method B: ArgEML -- 3.3 Evaluation Metrics -- 4 Results -- 4.1 Learning Method A -- 4.2 Learning Method B: ArgEML -- 4.3 Evaluation of the Learning Methods -- 5 Discussion.; 6 Concluding Remarks -- References -- General Vision - AI Applications -- Biometric Recognition of African Clawed Frogs -- 1 Introduction -- 2 Background and Related Work -- 3 Methodology -- 3.1 Data Acquisition -- 3.2 Pattern Extraction -- 3.3 Contour Delineation -- 4 Experiments -- 4.1 Data Set -- 4.2 Experimental Setup -- 4.3 Results -- 5 Discussion -- 6 Conclusion -- References -- Teacher-Student Synergetic Knowledge Distillation for Detecting Alcohol Consumption in NIR Iris Images -- 1 Introduction -- 2 Related Works -- 3 Research Methodology -- 3.1 Dataset Description -- 3.2 Feature Extractor -- 4 Experimental Analysis -- 4.1 Experimental Setup -- 4.2 Experimental Results -- 5 Conclusion and Future Works -- References -- Performance Assessment of Fine-Tuned Barrier Recognition Models in Varying Conditions -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Data Collection -- 3.2 Model Training -- 4 Experimental Results -- 5 Conclusion -- References -- Keyrtual: A Lightweight Virtual Musical Keyboard Based on RGB-D and Sensors Fusion -- 1 Introduction -- 2 Related Work -- 2.1 Non-wearable Hand-Based Interaction -- 2.2 Natural Virtual Interfaces for Music -- 3 Proposed Method -- 3.1 Preliminary Phase -- 3.2 Real-Time Phase -- 4 Experimental Environment -- 4.1 Experimental Setup -- 4.2 Experiments Execution -- 4.3 Results -- 5 Conclusions -- References -- Classification of Honey Pollens with ImageNet Neural Networks -- 1 Introduction -- 2 Materials and Methods -- 2.1 Ground Truth -- 2.2 ImageNet Networks -- 3 Experimental Work -- 3.1 Results per Types and Multiclass Metrics -- 4 Conclusions and Discussion -- References -- Defocus Blur Synthesis and Deblurring via Interpolation and Extrapolation in Latent Space -- 1 Introduction -- 2 Proposed Method -- 2.1 Imposing Linearity onto Latent Space -- 2.2 Evaluation Metrics.; 3 Experiments and Results -- 3.1 Dataset -- 3.2 Architecture and Training -- 3.3 Results -- 4 Discussion and Future Work -- 5 Conclusions -- References -- Unsupervised State Representation Learning in Partially Observable Atari Games -- 1 Introduction -- 2 Related Work -- 3 Method -- 4 Experimental Details -- 5 Results -- 6 Discussion -- 7 Conclusion -- References -- Structural Analysis of the Additive Noise Impact on the -tree -- 1 Introduction -- 2 Hierarchical Representations -- 2.1 The -tree Representation -- 2.2 Persistent Hierarchies -- 3 Noise Impact on the Tree Structure -- 3.1 Study on a Noisy Constant Image -- 3.2 Comparison with Natural Images -- 4 Impact of the Noise on Nodes Persistence -- 5 Conclusion and Perspectives -- References -- Augmented Reality for Indoor Localization and Navigation: The Case of UNIPI AR Experience -- 1 Introduction -- 2 Related Work -- 3 Design and Implementation -- 3.1 Background Technologies -- 3.2 Methodology -- 3.3 System Overview -- 3.4 Implementation -- 4 Results -- 4.1 System in Practice -- 4.2 Experimentation -- 5 Discussion -- 6 Conclusion -- References -- A Benchmark and Investigation of Deep-Learning-Based Techniques for ; Detecting Natural Disasters in Aerial Images -- 1 Introduction -- 2 Background and Related Work -- 3 Proposed Approach -- 3.1 Dataset for Disaster Recognition Using UAVs -- 3.2 Disaster Recognition Network Architecture -- 3.3 Baseline Designs -- 3.4 Data Pre-processing and Training Process -- 3.5 Explainability Through Grad-CAM -- 4 Experimental Evaluation and Results -- 4.1 Configuration and Evaluation Metrics -- 4.2 Disaster Classification Evaluation -- 4.3 Gram-CAM Evaluation -- 5 Conclusion and Future Work -- References -- Perceptual Light Field Image Coding with CTU Level Bit Allocation -- 1 Introduction -- 2 The Proposed Method.; 2.1 Designed CTU Level Bit Allocation Strategy with Perceptual Consistency.