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Progress in Image Processing, Pattern Recognition and Communication Systems : Proceedings of the Conference (CORES, IP&C, ACS) - June 28-30 2021
| Progress in Image Processing, Pattern Recognition and Communication Systems : Proceedings of the Conference (CORES, IP&C, ACS) - June 28-30 2021 |
| Autore | Choraś Michal |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing AG, , 2021 |
| Descrizione fisica | 1 online resource (362 pages) |
| Altri autori (Persone) |
ChoraśRyszard S
KurzyńskiMarek TrajdosPaweł PejaśJerzy HylaTomasz |
| Collana | Lecture Notes in Networks and Systems Ser. |
| Soggetto genere / forma | Electronic books. |
| ISBN | 3-030-81523-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- International Conference on Image Processing and Communications (IP& -- C 2021) -- General Chairs -- Local Chair -- Program Committee -- International Conference on Computer Recognition Systems (CORES 2021) -- Honorary Chair -- Chairs -- Program Committee -- Organization Committee Chair -- Organization Committee -- International Conference on Advanced Computer Systems (ACS 2021) -- Conference Chairs -- Organization Committee -- Program Committee -- Contents -- Advances in Pattern Recognition and Classifiers -- Building an Ensemble of Classifiers via Randomized Models of Ensemble Members -- 1 Introduction -- 2 Competence of Base Classifier -- 2.1 Preliminaries -- 2.2 Competence via Randomization -- 3 The Proposed Model of Competence -- 3.1 The Mathematical Fundamentals -- 3.2 Empirical Case -- 3.3 Competence Set -- 3.4 Generalization Method - Potential Function Model -- 4 Multiclassifier System with des Scheme -- 5 Experiments -- 5.1 Experimental Setup -- 5.2 Results and Discussion -- 6 Conclusions -- References -- Hybrid Learning Model for Syntactic Pattern Recognition -- 1 Introduction -- 2 Model of Vague Language Parsing -- 3 Neural Network as Vague Structural Pattern Generator -- 4 DPLL(k) Grammar Inference Scheme -- 5 Application for STLF -- 6 Concluding Remarks -- References -- Distance Metrics in Clusteringpg and Weighted Scoring Algorithm -- 1 Introduction -- 2 Clustering and Weighted Scoring Based on Estimating the Number of Clusters Algorithm -- 3 Experimental Evaluation -- 3.1 Setup -- 4 Results -- 4.1 Lessons Learned -- 5 Conclusions -- References -- Exploration of Hardware Acceleration Methods for an XNOR Traffic Signs Classifier -- 1 Introduction -- 2 Previous Work -- 3 Traffic Sign Classification with XNOR Networks -- 3.1 Custom Architecture -- 3.2 FINN Architecture -- 4 Hardware Acceleration.
4.1 Custom Accelerator -- 4.2 FINN Accelerator -- 5 Comparison of the Considered Approaches -- 6 Summary -- References -- ALEA: An Anonymous Leader Election Algorithm for Synchronous Distributed Systems -- 1 Introduction -- 1.1 Related Work -- 1.2 Contribution -- 2 The ALEA Algorithm -- 2.1 Assumptions -- 2.2 Terminology Used in the Algorithm -- 2.3 The ALEA Algorithm: Step by Step -- 2.4 Resolving Ties Among the Candidate Nodes -- 3 ALEA's Main Properties -- 4 Experimental Evaluation -- 4.1 Scenario -- 4.2 Experimental Results -- 5 Discussion -- 6 Conclusions -- References -- Progress in Image Processing and Computer Vision -- Comparing Concepts of Quantum and Classical Neural Network Models for Image Classification Task -- 1 Introduction -- 2 Materials and Methods -- 2.1 Quantum Computing -- 3 Experimental Framework -- 3.1 MNIST Data Set Split -- 3.2 Class Label Determination -- 3.3 Sub-sampling -- 3.4 Quantum Data Representation -- 3.5 Building a Model of a Quantum Neural Network -- 3.6 Building a Model of Classical Neural Network -- 3.7 Training, Validation, and Testing -- 3.8 Results -- 4 Discussion and Conclusions -- References -- Can Color Visual Cryptography Be Truly Random? -- 1 Introduction -- 2 Previous Methods -- 3 Truly Random Coding -- 4 Examples with Natural Images -- 5 A Note on Image Quality -- 6 Randomness Tests -- 7 Conclusion -- References -- Description-Based Ranking of Visual Instances: Feasibility Study for Keypoints -- 1 Introduction -- 2 Formal Model -- 2.1 Parametrization of Image Distortions -- 2.2 Keypoint Ranking -- 3 Experimental Verification -- 3.1 Test Scenario -- 3.2 Keypoint Ranking Experiments -- 3.3 Keypoint Matching Experiments -- 4 Summary -- References -- Fuzzy System for Lip Print Identification -- 1 Introduction -- 2 Lip Print -- 3 System Structure -- 3.1 Rule Base of the Proposed System. 3.2 Configuration of Premises and Facts -- 3.3 Results -- 4 Conclusions -- References -- Assessment of Correlations Between Age and Textural Features of CT Images of Thoracic Vertebrae -- 1 Introduction -- 2 Materials and Methods -- 3 Experimental Results -- 4 Discussion -- References -- Preprocessing of Document Images Based on the GGD and GMM for Binarization of Degraded Ancient Papyri Images -- 1 Introduction -- 2 Related Works -- 3 Image Preprocessing Based on the GGD and GMM -- 4 Discussion of Experimental Results -- 5 Conclusions and Future Work -- References -- Application of Image Entropy Analysis for the Quality Assessment of Stitched Images -- 1 Introduction -- 2 Brief Overview of Stitched Image Quality Assessment -- 3 Proposed Extension and Its Experimental Verification -- 4 Conclusions and Future Work -- References -- Practical Applications of Computer Recognition Systems -- Gyroscope-Based Remote Text Entry Interface -- 1 Introduction -- 2 Interface Concept -- 3 Examined Modes of Text Entry -- 4 Evaluation -- 5 Summary -- References -- Comparison of the Effects of Different Preprocessing Methods on Homogeneity Assessment of Digital Intraoral Radiographs of Root Canal Fillings -- 1 Introduction -- 2 Materials and Methods -- 2.1 Used Data -- 2.2 Methods -- 3 Results and Discussion -- References -- Impact of Software Bug Report Preprocessing and Vectorization on Bug Assignment Accuracy -- 1 Introduction -- 2 Related Works -- 3 Natural Language Processing Pipeline -- 3.1 Typical Natural Language Processing Pipeline -- 3.2 Preprocessing Methods -- 3.3 Vectorization Methods -- 4 Numerical Experiments -- 4.1 Research Questions -- 4.2 Description and Experimental Protocol -- 4.3 Results and Lessons Learned -- 5 Summary -- References -- On Machine Learning for Autism Prediction from Functional Connectivity -- 1 Introduction. 2 Materials and Methods -- 2.1 The Dataset -- 2.2 Brain Parcellations -- 2.3 Connectivity Matrices -- 2.4 Classifier Model Building Methods -- 2.5 Feature Extraction -- 2.6 Feature Selection -- 2.7 Classification Performance Report -- 3 Results and Discussion -- 4 Conclusions -- References -- The Impact of Data Preprocessing on the Accuracy of CNN-Based Heart Segmentation -- 1 Introduction -- 2 Related Works -- 3 Materials and Methods -- 3.1 Data -- 3.2 SDA -- 3.3 U-Net -- 3.4 Evaluation -- 4 Results -- 5 Conclusions -- References -- Comparison of Selected Acoustic Signal Parameterization Methods in the Problem of Machine Recognition of Classical Music Styles -- 1 Introduction -- 2 Database Development -- 2.1 Main Assumptions -- 3 Data Extraction -- 3.1 Spectrogram -- 3.2 Mel Scale Spectrogram -- 3.3 Mel-Cepstral Parameters -- 3.4 Chromagram -- 4 Computational Experiments -- 4.1 Data Preprocessing -- 4.2 Neural Network Training and Test Results -- 5 Summary -- References -- The Influence of Bit-Depth Reduction on Correlation of Texture Featurespg with a Patient's Age -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 X-Rays of Women's Cervical Spine -- 3.2 X-Rays of Men's Cervical Spine -- 4 Conclusions -- References -- Advances in ML for Security and Networks -- Deep Learning vs. Traditional Approaches to Malware Traffic Classification - A Comparative Study -- 1 Introduction -- 2 Related Works and Reference Method -- 3 Application of Classic Classifiers -- 3.1 Naïve Bayes -- 3.2 Decision Tree -- 4 Classification Results -- 4.1 Evaluation Scenario -- 4.2 Results Comparison -- 5 Conclusions -- References -- Using Machine Learning to Detect the Signs of Radicalization and Hate Speech on Twitter -- 1 Introduction -- 2 Hate Speech, Machine Learning and Sentiment Analysis -- 2.1 Radicalization and Hate Speech -- 2.2 Sentiment Analysis. 2.3 Word Embeddings and Word2Vec -- 2.4 LSTM and Other Neural Networks Used for Sentiment Analysis -- 2.5 State of the Art -- 3 Experimental Setup -- 3.1 The Data Used for Experiment -- 3.2 The Tool's Architecture -- 4 Conclusions -- References -- Clutter-Type Classification of the Telco BTS Units with the Use of Limited Input Information -- 1 Introduction -- 2 Problem Significance -- 3 Mobile Network Data Characteristics -- 4 Results -- 4.1 Experimental Protocol -- 4.2 Preliminary Studies - BTS Level -- 4.3 Results - Cell Level Inference -- 5 Conclusions -- References -- Cyber-Attack Detection from IoT Benchmark Considered as Data Streams -- 1 Introduction -- 2 IoT-23 Dataset as Data Stream -- 3 Experimental Evaluation -- 3.1 Results of the Experiment -- 4 Conclusions -- References -- Some Principles of Building Steganographic Communication Networks -- 1 Introduction -- 2 Problem Solving -- 2.1 General Statements -- 2.2 Application Level -- 2.3 Presentation Level -- 2.4 Stegosession Level -- 2.5 Stegotransport Level -- 2.6 Stegonetwork Level -- 2.7 Stegochannel Level -- 2.8 Stegocontainer Level -- 2.9 Example of Steganographic Communication Network Implementation -- 3 Conclusion -- References -- SAT-Based Cryptanalysis of Salsa20 Cipher -- 1 Introduction -- 2 Salsa20 -- 2.1 Operations on 4-Byte Words Used in Salsa20 -- 3 Boolean Encoding and SAT Based Cryptoanalysis -- 3.1 Cryptoanalysis Procedure -- 4 Experimental Results -- 5 Conclusion and Future Work -- References -- Smart Meters Reading Process Improvement by UAV Utilization -- 1 Introduction -- 2 State of the Art -- 3 Communication Scheme Used in RF Last Mile Networks for SMs Reading -- 4 Research Process and Methods -- 5 Space Track Determination Algorithm -- 6 Experimental Results -- 7 Conclusion -- References. Defuzzification Method Comparison in Real Data Packets Control Method for Network Protection. |
| Altri titoli varianti | Progress in Image Processing, Pattern Recognition and Communication Systems |
| Record Nr. | UNINA-9910497110503321 |
Choraś Michal
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| Cham : , : Springer International Publishing AG, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Progress on Pattern Classification, Image Processing and Communications : Proceedings of the CORES and IP&C Conferences 2023
| Progress on Pattern Classification, Image Processing and Communications : Proceedings of the CORES and IP&C Conferences 2023 |
| Autore | Burduk Robert |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (241 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
ChoraśMichał
KozikRafał KsieniewiczPaweł MarciniakTomasz TrajdosPaweł |
| Collana | Lecture Notes in Networks and Systems Series |
| ISBN | 3-031-41630-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Advanced Data Analysis and Machine Learning -- A Novel Approach of Multi-string Parsing for Syntactic Pattern Recognition -- 1 Introduction -- 2 Methodological Motivation -- 3 Preliminaries -- 4 Multi-string Parsing -- 5 Concluding Remarks -- References -- Hollow n-grams Vectorizer for Natural Language Processing Problems -- 1 Introduction -- 2 Hollow n-grams -- 3 Experiments Design -- 4 Experimental Evaluation -- 4.1 Experiment 1 - Max Features Threshold -- 4.2 Experiment 2 - Different nn values -- 5 Conclusions and Future Works -- References -- A Non-deep Approach to Classifying Movie Genres Based on Multimodal Data -- 1 Introduction -- 2 Related Works -- 3 Data Preprocessing and Extraction -- 4 Experimental Evaluation -- 4.1 Set-Up -- 4.2 Experiment 1 - Classification Comparison for Each Modality Separately -- 4.3 Experiment 2 - Classification Comparison for Multi-modal Data -- 4.4 Experiment 3 - Impact of Preprocessing on Distance-Based Classifiers Performance -- 5 Conclusion -- References -- Incremental Extreme Learning Machine for Binary Data Stream Classification -- 1 Introduction -- 2 Methods -- 3 Evaluation of Data Stream Classifiers -- 3.1 Experimental Setup -- 4 Experimental Evaluation -- 4.1 ELMi Hyperparameters -- 4.2 Comparison of Classifiers -- 5 Conclusions -- References -- Interpreting Intrusions - The Role of Explainability in AI-Based Intrusion Detection Systems -- 1 Introduction, Motivation and Rationale -- 2 Materials and Methods -- 2.1 Advantages and Limitations of xAI Techniques -- 2.2 Overview of xAI Techniques Applicable in Intrusion Detection -- 3 Experimental Setup and Results -- 3.1 xAI Interpretation -- 4 Conclusions -- References -- Real-Time Deformation of Three-Dimensional Volumetric Models Using Mesh Models -- 1 Introduction -- 2 Motivations.
3 Deformation Simulation -- 3.1 Obi Based Simulation -- 3.2 3D Volume Deformation -- 4 Results and Discussion -- References -- Hyperparameters Optimization Using GridSearchCV Method for TinyML Models -- 1 Introduction -- 2 GridSearchCV Method -- 3 TGrid Algorithm -- 4 Experiments -- 5 Conclusions -- References -- Analysis of the Possibility to Employ Relationship Between the Problem Complexity and the Classification Quality as Model Optimization Proxy -- 1 Introduction -- 1.1 Related Works -- 1.2 Contribution -- 2 Purposes of the Experiment -- 2.1 Experiment 1: Single Criterion Optimization -- 2.2 Experiment 2: Dependency Research for Resampling Methods -- 3 Experimental Evaluation -- 3.1 Experiment 1: Single Criterion Optimization -- 3.2 Experiment 2: Dependency Research for Resampling Methods -- 4 Conclusion -- References -- Image Processing -- Deep Learning for Pit Detection in Cherries -- 1 Introduction -- 2 Image Acquisition System -- 3 Datasets -- 4 Image Analysis Method -- 5 Experiments -- 5.1 Polarization Parameters in Classification -- 5.2 Combining Information for Better Prediction -- 6 Summary -- References -- Image Analysis System for Augmented Reality Games -- 1 Introduction -- 2 General Concept -- 2.1 Detection and Tracking Module -- 2.2 Global Re-ID -- 2.3 Action Recognition -- 3 Experiments -- 4 Conclusions -- References -- Coregistration of Selected Sequences in MRI Imaging Based on Edge Analysis of Image Difference -- 1 Introduction -- 2 Materials and Methods -- 2.1 The Dataset -- 2.2 Designed Procedure -- 2.3 Reference Measures of Image Alignment -- 2.4 Results -- 3 Summary -- References -- Actinic Keratosis Prediction Based on Deep Learning Methods -- 1 Introduction -- 1.1 Deep Leaning for AK Classification -- 1.2 Deep Leaning for AK Detection -- 2 Methods -- 2.1 Data Collection -- 2.2 Data Preprocessing and Augmentation. 2.3 Object Detection Model -- 2.4 Performance Metrics -- 2.5 Model Interpretation -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- A New Assessment of Convolutional Neural Networks for Texture Directionality Detection -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Enhanced Training Data -- 3.2 Novel CNN Architectures and Additional Activation Functions -- 4 Results and Discussion -- 5 Conclusions and Future Work -- References -- Knowledge Distillation with Relative Representations for Image Representation Learning -- 1 Introduction -- 2 Related Work -- 3 Background: Relative Representations -- 4 Relative Representation Distillation -- 5 Experiments -- 5.1 Distillation Compared to Training from Scratch -- 5.2 Comparison to Other Relation-Based Distillation Methods -- 5.3 Transfer Learning -- 5.4 Anchor Selection -- 6 Conclusion -- References -- An Approach for CT Image Conversion Using Filtering Based on Quaternion Mathematics -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Bilateral Filter -- 3.2 Quaternion Mathematics -- 4 Quaternion Bilateral Filter (QBF) -- 5 Experimental Results -- 5.1 Evaluation Metrics -- 5.2 Results -- 6 Conclusion -- References -- Exploring Text-Guided Synthetic Distribution Shifts for Robust Image Classification -- 1 Introduction -- 2 Related Work -- 3 Distribution-Shifted Data Generation -- 4 Experiments -- 4.1 Implementation -- 4.2 Measuring Distribution Shift -- 4.3 Probing Adversarial Ability -- 4.4 Use as Training Data -- 5 Conclusion -- References -- Artificial Intelligence: Various Applications and Problems -- Color Tracking Application Using AI-Based Docker Container Scheduling in Fog Computing -- 1 Introduction -- 2 FogBus2 Framework -- 2.1 Multiplatform Support -- 2.2 Containerization Support -- 2.3 Heterogeneous IoT Applications -- 2.4 Distributed Multi-database. 2.5 Integration with Cloud Infrastructure and VPN -- 2.6 Dynamic Scheduling Mechanism and Policy Integration -- 3 Communications Among Components -- 4 Proposed Solution for Container Scheduling in Cloud Computing -- 5 Experimental Results -- 5.1 Developed Edge Computing Network -- 5.2 Experimental Environment -- 5.3 Experimental Results -- 6 Conclusions and Future Actions -- References -- Air Pollution Monitoring and Information Distribution System -- 1 Introduction -- 2 Proposed System -- 2.1 System Structure -- 2.2 Vehicle -- 2.3 Instruments -- 2.4 Results -- 3 Conclusion -- References -- Detection of Conspiracy Theories from Tweets Using NLI-Based Zero Shot Text Classification Models -- 1 Introduction -- 2 Related Works -- 3 Proposed Data Pipeline -- 3.1 Data Collection -- 3.2 Models -- 4 Analysis -- 4.1 Data Analysis -- 4.2 Controversy Analysis -- 4.3 Sentiment Analysis -- 5 Conclusions -- References -- Battery Management System for Polish Hybrid Residential Photovoltaic Power Plants -- 1 Introduction -- 2 Self-consumption Battery Management System -- 3 Time-Based Battery Management System -- 4 Experiments -- 5 Conclusions -- References -- Document Annotation Tool for News Content Analysis -- 1 Introduction -- 2 Proposed Tool for Content Annotation -- 3 Results Analysis -- 4 Conclusions -- References -- Dynamic Time Warping Technique Applied to the User's Intent Recognition for Myoelectric-Based Control of Upper Limb Prosthesis -- 1 Introduction -- 2 Methods -- 3 Experimental Setup -- 4 Results and Discussion -- 4.1 Experiment 1 -- 4.2 Experiment 2 -- 5 Conclusions -- References -- A Hybrid Long Short-Term Memory Network Based on Wind and Rain Sensitive and Its Application to PM2.5 Prediction -- 1 Introduction -- 2 Related Work -- 2.1 Air Pollution Forecasting and Air Pollution Factors -- 2.2 Time Series Problem -- 3 Proposed Approach. 3.1 Overview -- 3.2 Data Preprocessing -- 3.3 Wind-Sensitive LSTM and Rain-Sensitive LSTM -- 4 Experiment and Evaluation -- 4.1 Dataset and Experiment Setup -- 4.2 Evaluation Metric -- 4.3 Compared Models -- 4.4 Evaluation of the Number of Past Time Periods for PM2.5 -- 4.5 Evaluation of All Comparison Models -- References -- Author Index. |
| Record Nr. | UNINA-9910767562003321 |
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Burduk Robert
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| Cham : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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