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Fifth international workshop on pattern recognition

Fifth International Workshop on Pattern Recognition

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5th international workshop on pattern recognition, IWPR 2020

ISBN: (纸本)9781510638631

the proceedings contain 18 papers. the topics discussed include: improved hierarchical models for non-native Chinese handwriting recognition using hidden conditional random fields;a framework for multimodal sign language recognition under small sample based on key-frame sampling;a classification method for rotor imbalance fault with ISFLA-SVM;facial expression recognition based on feature fusion;improving visual question answering with pre-trained language modeling;feature detection based on linear prediction residual for spoofing countermeasures of speaker verification system;classification of defaced occlusion plates based on convolutional neural network;research of road scene object detection algorithm based on mobile platform;and improved YOLO model with multi-feature fully convolutional network for object detection.

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Fingerprints recognition System-based on Mobile Device Identification Using Circular String pattern Matching Techniques 9th

Fingerprints Recognition System-Based on Mobile Device Ident...

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16th IFIP WG 12.5 international Conference on Artificial Intelligence Applications and Innovations (AIAI) / 9th Mining Humanistic Data workshop (MHDW) / 5th workshop on 5G-Putting Intelligence to the Network Edge (5G-PINE)

作者： Alshammary, Miznah H. Iliopoulos, Costas S. Khan, Mujibur R. Kings Coll London Dept Informat London England

ISBN: (纸本)9783030491925;9783030491901;9783030491895

As fingerprint recognition systems have become increasingly adopted within a range of technology applications over the last decade, so too has their attention within emerging research. However, although this increased attention has led to an enhancement of the software and algorithms behind this recognition process, the majority of research has still not addressed the issues of incorrect rotation or proximity between the finger and the device. Current systems assume that the direction of the imprinted finger will align with that of the target fingerprint image;this decreases the accuracy of fingerprint recognition across a variety of finger orientations and scenarios. In response to this use-case dilemma, this paper proposes a new technique of pattern matching that can account for this natural range of fingerprint orientations. this is achieved first through a preliminary stage of orientation identification, whereby the fingerprint image can be stored under multiple permutations by using approximate circular string-matching algorithms. this enables the database of images for each approximate permutation of orientation to be stored in advance. It can then be matched against the strong information of the fingerprint at its exact relative rotation of input. the improved accuracy of recognition demonstrated through the results of this study may enable the functionality of fingerprint recognition to adapt to challenging device form-factors and provide the accuracy needed for military and medical applications.

关键词： Mobile device fingerprinting Fingerprint recognition Rotation Circular string matching

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9th Mining Humanistic Data workshop, MHDW 2020, and the 5th workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2020, held as parallel events of the 16th IFIP WG 12.5 international Conference on Artificial Intelligence Applications and Innovations, AIAI 2020

9th Mining Humanistic Data Workshop, MHDW 2020, and the 5th ...

引用

9th Mining Humanistic Data workshop, MHDW 2020, and the 5th workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2020, held as parallel events of the 16th IFIP WG 12.5 international Conference on Artificial Intelligence Applications and Innovations, AIAI 2020

ISBN: (纸本)9783030491895

the proceedings contain 21 papers. the special focus in this conference is on Mining Humanistic Data. the topics include: threat Landscape of Next Generation IoT-Enabled Smart Grids;towards a Smart Port: the Role of the Telecom Industry;a graph-based Extension for the Set-based Model Implementing Algorithms based on Important Nodes;a Sentiment-based Hotel Review Summarization Using Machine Learning Techniques;an Advanced Deep Learning Model for Short-Term Forecasting U.S. Natural Gas Price and Movement;fake News Detection Regarding the Hong Kong Events from Tweets;improving Movie Recommendation Systems Filtering by Exploiting User-based Reviews and Movie Synopses;the Converging Triangle of Cultural Content, Cognitive Science, and Behavioral Economics;application and Algorithm: Maximal Motif Discovery for Biological Data in a Sliding Window;A New Approach to 5G and MEC Integration;fingerprints recognition System-based on Mobile Device Identification Using Circular String pattern Matching Techniques;mining and Analysis of Air Quality Data to Aid Climate Change;business Aspects of the Neutral Host Model: the Immersive Video Services Case;combined 5G-based Video Production and Distribution in a Crowded Stadium Event;dynamic Network Slicing: Challenges and Opportunities;dynamic Resource Allocation and Computation Offloading for Edge Computing System;Intelligent Orchestration of End-to-End Network Slices for the Allocation of Mission Critical Services over NFV Architectures;on the Prediction of Future User Connections based on Historical Records in Wireless Networks;Programmable Edge-to-Cloud Virtualization for 5G Media Industry: the 5G-MEDIA Approach.

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Comparisons of two approaches of pattern recognition for text detection 5

Comparisons of two approaches of pattern recognition for tex...

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5th Symposium for Young Scientists in Technology, Engineering and Mathematics, SYSTEM 2020

作者： Lis, Ewa Kluger, Roman Faculty of Applied Mathematics Silesian University of Technology Kaszubska 23 Gliwice44-100 Poland

the paper describes two methods of pattern recognition, one based on soft sets, another based on neural networks. Soft set theory is quite recently developed method of AI. that approach has rather simple mathematical background, but can perform satisfactory. Widespread neural network approach demands much more calculating power to perform at the same level of accuracy. Some hints to make neural network perform better have been written. Authors explain necessary theoretical terms and definitions then describe their idea of two AI systems. At the end some results of first system are presented. © 2020 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 international (CC BY 4.0).

关键词： Character recognition

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Structured (de)composable representations trained with neural networks 9th

Structured (de)composable representations trained with neura...

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9th IAPR TC3 international workshop on Artificial Neural Networks in pattern recognition, ANNPR 2020

作者： Spinks, Graham Moens, Marie-Francine Department of Computer Science KU Leuven Leuven Belgium

ISBN: (纸本)9783030583088

the paper proposes a novel technique for representing templates and instances of concept classes. A template representation refers to the generic representation that captures the characteristics of an entire class. the proposed technique uses end-to-end deep learning to learn structured and composable representations from input images and discrete labels. the obtained representations are based on distance estimates between the distributions given by the class label and those given by contextual information, which are modeled as environments. We prove that the representations have a clear structure allowing to decompose the representation into factors that represent classes and environments. We evaluate our novel technique on classification and retrieval tasks involving different modalities (visual and language data). © 2020, the Author(s).

关键词： Deep learning

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Cross-Evaluation of graph-based Keyword Spotting in Handwritten Historical Documents 1

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12th IAPR-TC15 workshop on graph-based representations in pattern recognition (GbRPR)

作者： Stauffer, Michael Maergner, Paul Fischer, Andreas Riesen, Kaspar Univ Appl Sci & Arts Northwestern Switzerland Inst Informat Syst Riggenbachstr 16 CH-4600 Olten Switzerland Univ Fribourg Dept Informat Blvd Perolles 90 CH-1700 Fribourg Switzerland Univ Appl Sci & Arts Western Switzerland Inst Complex Syst Blvd Perolles 80 CH-1700 Fribourg Switzerland

ISBN: (数字)9783030200817

ISBN: (纸本)9783030200817;9783030200800

In contrast to statistical representations, graphs offer some inherent advantages when it comes to handwriting representation. that is, graphs are able to adapt their size and structure to the individual handwriting and represent binary relationships that might exist within the handwriting. We observe an increasing number of graph-based keyword spotting frameworks in the last years. In general, keyword spotting allows to retrieve instances of an arbitrary query in documents. It is common practice to optimise keyword spotting frameworks for each document individually, and thus, the overall generalisability remains somehow questionable. In this paper, we focus on this question by conducting a cross-evaluation experiment on four handwritten historical documents. We observe a direct relationship between parameter settings and the actual handwriting. We also propose different ensemble strategies that allow to keep up with individually optimised systems without a priori knowledge of a certain manuscript. Such a system can potentially be applied to new documents without prior optimisation.

关键词： Keyword spotting Handwritten historical documents graph-based representations Hausdorff Edit Distance Ensemble methods

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Dataset of Pages from Early Printed Books with Multiple Font Groups 19

Dataset of Pages from Early Printed Books with Multiple Font...

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5th international workshop on Historical Document Imaging and Processing (HIP)

作者： Seuret, Mathias Limbach, Saskia Weichselbaumer, Nikolaus Maier, Andreas Christlein, Vincent Friedrich Alexander Univ Pattern Recognit Lab Erlangen Germany Gutenberg Inst Weltliteratur & Schriftorient Medi Abt Buchwissensch Mainz Germany

ISBN: (纸本)9781450376686

based on contemporary scripts, early printers developed a large variety of different fonts. While fonts may slightly differ from one printer to another, they can be divided into font groups, such as Textura, Antiqua, or Fraktur. the recognition of font groups is important for computer scientists to select adequate OCR models, and of high interest to humanities scholars studying early printed books and the history of fonts. In this paper, we introduce a new, public dataset for the recognition of font groups in early printed books, and evaluate several state-of-the-art CNNs for the font group recognition task. the dataset consists of more than 35 600 page images, each page showing up to five different font groups, of which ten are considered in this dataset.

关键词： uments document analysis incunabula book history type typography fonts Antiqua Italic Textura Rotunda Gotico-Antiqua Bastarda Schwabacher Fraktur Greek Hebrew

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2nd international workshop on Recent Advances in Digital Security: Biometrics and Forensics, BioFor 2019, 1st international workshop on pattern recognition for Cultural Heritage, PatReCH 2019, 1st international workshop eHealth in the Big Data and Deep Learning Era, e-BADLE 2019, international workshop on Deep Understanding Shopper Behaviors and Interactions in Intelligent Retail Environments, DEEPRETAIL 2019 and Industrial session held at the 20th international Conference on Image Analysis and Processing, ICIAP 2019

2nd International Workshop on Recent Advances in Digital Sec...

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2nd international workshop on Recent Advances in Digital Security: Biometrics and Forensics, BioFor 2019, 1st international workshop on pattern recognition for Cultural Heritage, PatReCH 2019, 1st international workshop eHealth in the Big Data and Deep Learning Era, e-BADLE 2019, international workshop on Deep Understanding Shopper Behaviors and Interactions in Intelligent Retail Environments, DEEPRETAIL 2019 and Industrial session held at the 20th international Conference on Image Analysis and Processing, ICIAP 2019

ISBN: (纸本)9783030307530

the proceedings contain 39 papers. the special focus in this conference is on Recent Advances in Digital Security. the topics include: Modern vs Diplomatic Transcripts for Historical Handwritten Text recognition;improving Ancient Cham Glyph recognition from Cham Inscription Images Using Data Augmentation and Transfer Learning;Oracle Bone Inscription Detector based on SSD;shot Boundary Detection for Automatic Video Analysis of Historical Films;the Epistle to Cangrande through the Lens of Computational Authorship Verification;a Cockpit of Measures for Image Quality Assessment in Digital Film Restoration;augmented Reality for the Valorization and Communication of Ruined Architecture;classification of Arabic Poems: from the 5th to the 15th Century;a Page-based Reject Option for Writer Identification in Medieval Books;on the Cross-Finger Similarity of Vein patterns;minimizing Training Data for Reliable Writer Identification in Medieval Manuscripts;fusion of Visual and Anamnestic Data for the Classification of Skin Lesions with Deep Learning;slide Screening of Metastases in Lymph Nodes via Conditional, Fully Convolutional Segmentation;A Learning Approach for Informative-Frame Selection in US Rheumatology Images;a Serious Game to Support Decision Making in Medical Education;nerve Contour Tracking for Ultrasound-Guided Regional Anesthesia;Skin Lesions Classification: A Radiomics Approach with Deep CNN;semantic 3D Object Maps for Everyday Robotic Retail Inspection;collecting Retail Data Using a Deep Learning Identification Experience;a Large Scale Trajectory Dataset for Shopper Behaviour Understanding;Improving Multi-scale Face recognition Using VGGFace2;An IOT Edge-Fog-Cloud Architecture for Vision based Pallet Integrity;the Vending Shopper Science Lab: Deep Learning for Consumer Research.

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Attribute Representation for Human Activity recognition of Manual Order Picking Activities 18

Attribute Representation for Human Activity Recognition of M...

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5th international workshop on Sensor-based Activity recognition and Interaction (iWOAR)

作者： Reining, Christopher Schlangen, Michelle Hissmann, Leon ten Hompel, Michael Moya, Fernando Fink, Gernot A. Tech Univ Dortmund Chair Mat Handling & Warehousing Dortmund Germany Tech Univ Dortmund Pattern Recognit Embedded Syst Grp Dortmund Germany

ISBN: (纸本)9781450364874

Semantic descriptions or attribute representations have been used successfully for object and scene recognition, and for word-spotting. However, these representations have not been explored deeply on human activity recognition (HAR). Particularly, in the manual order picking process, attribute representations are beneficial for dealing with the versatility of activities in the process. this paper compares the performance of deep architectures trained using different attribute representations for HAR. Besides, it evaluates their quality from the perspective of practical application.

关键词： Human Activity recognition (HAR) Deep Learning Attribute-based Representation Order Picking Motion Capturing

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Mobile Assisted Living: Smartwatch-based Fall Risk Assessment for Elderly People 18

Mobile Assisted Living: Smartwatch-based Fall Risk Assessmen...

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5th international workshop on Sensor-based Activity recognition and Interaction (iWOAR)

作者： Haescher, Marian Matthies, Denys J. C. Srinivasan, Karthik Bieber, Gerald Fraunhofer Inst Comp Graph Res IGD Rostock Rostock Germany Univ Auckland Auckland Bioengn Inst Augmented Human Lab Auckland New Zealand Next Step Dynam AB Malmo Sweden

ISBN: (纸本)9781450364874

We present a novel Smartwatch-based approach, to enable Mobile Assisted Living (MAL) for users with special needs. A major focus group for this approach are elderly people. We developed a tool for caregivers applicable in home environments, nursing care, and hospitals, to assess the vitality of their patients. Hereby, we particularly focus on the prediction of falls, because falls are a major reason for serious injuries and premature death among elderly. therefore, we propose a multi parametric score based on standardized fall risk assessment tests, as well as on sleep quality, medication, patient history, motor skills, and environmental factors. the resulting total fall risk score reflects individual changes in behavior and vitality, which consequently enables for fall preventing interventions. Our system has been deployed and evaluated in a pilot study among 30 elderly patients over a period of four weeks.

关键词： Mobile Assisted Living Fall Risk Assistance Elderly People Smartwatch Health Care Health Technology Pulse Detection Vital Signs pattern recognition

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