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检索条件"任意字段=8th International Conference on Computing and Pattern Recognition, ICCPR 2019"

共 395 条记录，以下是111-120 订阅

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Twitter user geolocation based on heterogeneous network and label propagation 8

Twitter user geolocation based on heterogeneous network and ...

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8th international conference on computing and pattern recognition, iccpr 2019

作者： Tian, Hechan Qiao, Yaqiong Liu, Yimin State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan*** China

ISBN: (纸本)9781450376570

Twitter user geolocation is applied into various applications, such as local messages recommendation and event location recognition. Existing methods do not usually utilize the potential positional correlation between heterogeneous information, resulting in low user geolocation accuracy. therefore, this paper proposes a user geolocation method based on heterogeneous network and label propagation. First, a heterogeneous network is built based on heterogeneous information mined from user tweets. then, by analyzing the factors that impact the efficiency and accuracy of label propagation, redundant nodes and edges in the initialized heterogeneous network are removed. Finally, the locations of unlabeled users are geolocated through label propagation in the simplified heterogeneous network. Experiments on the publicly available Twitter benchmark dataset show that proposed method accurately locate 57% of users within 161 km of their locations, a significant improvement over several existing methods. © 2019 Association for computing Machinery.

关键词： Heterogeneous networks

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A New Distance Measure Between Atanassov’s Intuitionistic Fuzzy Sets Based on Mapping 15th

A New Distance Measure Between Atanassov’s Intuitionistic F...

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15th international conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2019, co-located with the 5th international conference on Harmony Search, Soft computing and Applications, ICHSA 2019

作者： Su, Fang Li, Jing Xiao, Dongxuan Duan, Chengrui School of Information and Telecommunication Engineering Beijing University of Posts and Telecommunication No. 10 Xitucheng Road Haidian District Beijing100876 China

ISBN: (纸本)9783030324551

A new trapezoidal approximation of Atanassov’s intuitionistic fuzzy sets (AIFSs) and a new distance measure between AIFSs based on the area relations of membership function graphs of their corresponding trapezoidal fuzzy sets are proposed. By the conversion from Atanassov’s intuitionistic fuzzy numbers (AIFNs) to trapezoidal fuzzy numbers, the measurement of distance between AIFSs can be transformed into the calculation of area relations of the corresponding trapezoidal fuzzy sets. then the new distance measurement can integrate continuous information rather than only taking discrete variables into consideration as before. the main innovation of our distance is that it can integrate comprehensive and continuous information in calculation instead of partial discrete variables, which can efficiently avoid information loss. the contrastive tests demonstrate the efficiency and practicality of the approach. © Springer Nature Switzerland AG, 2020.

关键词： pattern recognition

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uPAD: Unsupervised Privacy-Aware Anomaly Detection in High Performance computing Systems 8th

uPAD: Unsupervised Privacy-Aware Anomaly Detection in High P...

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8th international conference on pattern recognition Applications and Methods (ICPRAM)

作者： Ghiasvand, Siavash Tech Univ Dresden Dresden Germany

ISBN: (纸本)9789897583513

Rapid growing complexity of HPC systems in response to demand for higher computing performance, results in higher probability of failures. Early detection of failures significantly reduces the damages caused by failure via impeding their propagation through system. Various anomaly detection mechanism are proposed to detect failures in their early stages. Insufficient amount of failure samples in addition to privacy concerns extremely limits the functionality of available anomaly detection approaches. Advances in machine learning techniques, significantly increased the accuracy of unsupervised anomaly detection methods, addressing the challenge of insufficient failure samples. However, available approaches are either domain specific, inaccurate, or require comprehensive knowledge about the underlying system. Furthermore, processing certain monitoring data such as system logs raises high privacy concerns. In addition, noises in monitoring data severely impact the correctness of data analysis. this work proposes an unsupervised and privacy-aware approach for detecting abnormal behaviors in general HPC systems. Preliminary results indicate high potentials of autoencoders for automatic detection of abnormal behaviors in HPC systems via analyzing anonymized system logs using fast-trainable noise-resistant models.

关键词： pattern Detection Time Series Analysis Anomaly Detection Neural Networks Noise Mitigation

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8th international conference on Communications, Signal Processing, and Systems, CSPS 2019

8th International Conference on Communications, Signal Proce...

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8th international conference on Communications, Signal Processing, and Systems, CSPS 2019

ISBN: (纸本)9789811394089

the proceedings contain 326 papers. the special focus in this conference is on Communications, Signal Processing, and Systems. the topics include: Research on Motor Speed Estimation Method Based on Electric Vehicle;A Novel Virtual Cell Power Allocation and Interference Merging Algorithm in UDN;device-Free Sensing for Gesture recognition by Wi-Fi Communication Signal Based on Auto-encoder/decoder Neural Network;detection of Sleep Apnea Based on Cardiopulmonary Coupling;study on a Space-Air-Ground Integrated Data Link Networks Architecture;similar Cluster Based Continuous Bag-of-Words for Word Vector Training;Research on Integrated Waveform of FDA Radar and Communication Based on Linear Frequency Offsets;research on Parameter Configuration of Deep Neural Network Applied on Speech Enhancement;mid-Infrared Characteristic Analysis of Stability Index of Vehicle Gasoline;coverage Probability Analysis of D2D Communication Based on Stochastic Geometry Model;application of Mid-Infrared Characteristic Analysis Technology in Gasoline Quality Control;A Generalized Sampling Based Method for Digital Predistortion of RF Power Amplifiers;Optimum Design of Intersatellite Link Based on STK;integrated Detection and Tracking in Asynchronous Moving Radar Network;fault-Tolerant Decompression Method of Compressed Chinese Text Files;Classification of Human Motion Status Using UWB Radar Based on Decision Tree Algorithm;A Sub-aperture Division Method for FMCW CSAR Imaging;an Experimental Study of Sea Target Detection of Passive Bistatic Radar Based on Non-cooperative Radar Illuminators;Design of a Quasi-Real-Time Communication System for LEO Satellites Using Beidou Short-Message Service;A Physically Decoupled Onboard Control Plane for Software Defined LEO Constellation Network;Study of Fault pattern recognition for Spacecraft Based on DTW Algorithm.

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Automatic Medicinal Plants Classification using Multi-channel Modified Local Gradient pattern with SVM Classifier 8

Automatic Medicinal Plants Classification using Multi-channe...

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Joint 8th international conference on Informatics, Electronics and Vision (ICIEV) / 3rd international conference on Imaging, Vision and pattern recognition (icIVPR) / international conference on Activity and Behavior computing (ABC)

作者： Habiba, Umme Howlader, Md Rasel Islam, Md Aminul Faisal, Rahat Hossain Rahman, Md Mostafijur Univ Barisal Dept Comp Sci & Engn Barisal Bangladesh

ISBN: (纸本)9781728107882

Most of the people in the world rely on traditional medicine which is made from medicinal plants. However, very few works concentrate on automatic classification. therefore, the automatic classification of medicinal plants demands more investigation which is an important issue for conservation, authentication, and production of medicines. In this paper, for automatically classifying medicinal plants, we present a Multi-channel Modified Local Gradient pattern (MCMLGP), a new texture-based feature descriptor that uses different channels of color images for extracting more significant features to improve the performance of classification. We have trained our proposed approach using SVM classifier with various kernels such as linear, polynomial and HI. In addition, we have used different feature descriptors for comparative experimental analysis with MCMLGP by conducting the rigorous experiment on our own medicinal plants dataset. the proposed approach gain higher accuracy (96.11%) than other techniques, and significantly valuable for exploration and evolution of medicinal plants classification.

关键词： Image Classification Medicinal plant LGP Adaptive threshold SVM

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Training Effective Model for Real-Time Detection of NSFW Photos and Drawings 8th

Training Effective Model for Real-Time Detection of NSFW Pho...

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8th international conference on Analysis of Images, Social Networks, and Texts (AIST)

作者： Zhelonkin, Dmirty Karpov, Nikolay Natl Res Univ Higher Sch Econ 25-12 Bolshaya Pechyorskaya Str Nizhnii Novgorod 603155 Russia

ISBN: (纸本)9783030395759;9783030395742

Convolutional Neural Networks (CNN) show state of the art results on variety of tasks. the paper presents the scheme how to prepare highly accurate (97% on the test set) and fast CNN for detection not suitable or safe for work (NSFW) images. the present research focuses on investigating questions concerning identifying NSFW pictures with nudity by neural networks. One of the main features of the present work is considering the NSFW class of images not only in terms of natural human nudity but also include cartoons and other drawn pictures containing obscene images of the primary sexual characteristics. Another important considered issue is collecting representative dataset for the problem. the research includes the review of existing nudity detection methods, which are provided by traditional machine learning techniques and quite new neural networks based approaches. In addition, several important problems in NSFW pictures filtering are considered in the study.

关键词： Image recognition pattern recognition Not suitable or safe for work Convolutional neural networks Pornography detection

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Neural Network-Based Vehicle and Pedestrian Detection for Video Analysis System 8

Neural Network-Based Vehicle and Pedestrian Detection for Vi...

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8th Mediterranean conference on Embedded computing (MECO) / Summer School on Cyber-Physical Systems and Internet-of-things (CPS and IoT)

作者： Babayan, Pavel V. Ershov, Maksim D. Erokhin, Denis Y. RSREU Dept Automat & Informat Technol Control Ryazan Russia

ISBN: (纸本)9781728117393

In our research we compare various neural network architectures that are used for object detection and recognition. In this work vehicles and pedestrians are considered objects of interest. Modern artificial neural networks are able to detect and localize objects of known classes. this allows them to be used in various technical vision systems and video analysis systems. In this paper we compare three architectures (YOLO, Faster R-CNN, SSD) by the following criteria: processing speed, mAP, precision and recall.

关键词： video analysis image processing object detection pattern recognition neural networks machine learning

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Accelerated Algorithm for Computation of All Prime patterns in Logical Analysis of Data 8th

Accelerated Algorithm for Computation of All Prime Patterns ...

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8th international conference on pattern recognition Applications and Methods (ICPRAM)

作者： Chambon, Arthur Lardeux, Frederic Saubion, Frederic Boureau, Tristan Univ Angers LERIA Angers France Univ Angers UMR1345 IRHS Angers France

ISBN: (纸本)9789897583513

the analysis of groups of binary data can be achieved by logical based approaches. these approaches identify subsets of relevant Boolean variables to characterize observations and may help the user to better understand their properties. In logical analysis of data, given two groups of data, patterns of Boolean values are used to discriminate observations in these groups. In this work, our purpose is to highlight that different techniques may be used to compute these patterns. We present a new approach to compute prime patterns that do not provide redundant information. Experiments are conducted on real biological data.

关键词： Logical Analysis of Data pattern Generation Logical Characterization of Data

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Annotation Matters: A Comprehensive Study on Recognizing Intended, Self-reported, and Observed Emotion Labels using Physiology 8

Annotation Matters: A Comprehensive Study on Recognizing Int...

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8th international conference on Affective computing and Intelligent Interaction (ACII)

作者： Yang, Hao-Chun Lee, Chi-Chun Natl Tsing Hua Univ Elect Engn Hsinchu Taiwan

ISBN: (纸本)9781728138886

Studies have shown that the formation of emotion as self-awareness and cognitive appraisal process is complicated and can lead to idiosyncratic differences. Subject's self emotion evaluation process could be biased due to factors of environment, personal experience, and one's own cognitive ability, and the true affective state may be neglected (un-noticeable) due to an unconscious mental process. In this work, we present a comprehensive study to investigate the emotion recognition accuracy obtained using physiology with respect to different annotation schemes, i.e., intended, self-reported, and observed emotion labels. We found that when performing recognition across these three different labeling schemes using the same physiological parameters, the accuracy of the self-reported emotion labels results in about 10.3% and 3.1% drop when compared to two other annotation schemes. It indicates that self-assessed emotion labels may be noisier and induces a larger mismatch with respect to the affect-stimulated physiological responses. Further analysis shows that the electrodermal activity signal has the highest recognition rate with respect to the intended emotion of the stimuli. Finally, our error analysis reveals that there may exist a bias in the self-annotated label that is conditioned on the intended stimuli's valence polarity.

关键词： emotion recognition annotation physiology affective computing mental process

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Social touch: stimuli-imitation protocol and automated recognition 8

Social touch: stimuli-imitation protocol and automated recog...

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8th international conference on Affective computing and Intelligent Interaction (ACII)

作者： Elbani, Wail Sorbonne Univ Inst Syst Intelligents & Robot CNRS UMR 7222 Paris France

ISBN: (纸本)9781728138916

Touch plays an important role in socio-emotional communication: a loving hug from a spouse, a comforting tap on the back by friend, a push from a stranger convey efficiently an emotion or an intent, specially when combined with other modalities such as audition and vision. In a parent-child relationship, the frequency of maternal touch is positively correlated to the a child early social development. In addition, Touch occurs frequently in patient care situation: a massage therapy, for instance, reduces chronic pain and alleviates anxiety when properly applied by a nurse. Underexplored by the human-machine-interaction and the affective computing literature, the purpose of this thesis is to integrate the sense of touch into interactive systems. In this paper we introduce a novel data collection framework for social touch and present the social touch recognition pipeline.

关键词： social touch touch gesture recognition imitation affective computing data collection

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