these days, Twitter social network is one of the main platforms for getting news, among people over the world. this is because of the high volume of data generated by this social media, which makes Twitter up to date ...
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ISBN:
(纸本)9781538653647
these days, Twitter social network is one of the main platforms for getting news, among people over the world. this is because of the high volume of data generated by this social media, which makes Twitter up to date with news and information. Nevertheless, the existence of invalid information over the social network makes the users unhappy and also arises some problems in the real world, particularly in the crisis. To overcome these problems and other possible issues, automatic detection of rumor on Twitter must be taken into account. Despite such issues, in this paper, rumor detection in Twitter is studied. In this paper, the rumor is validated by considering the user's feedback, as the source data for rumor study. In our proposed method, patternrecognition and its analysis of the user conversational tree in Twitter is studied. these recognized patterns feed into as features for training a classifier for rumor detection. the model for training a classifier is an Extreme Learning Machine and its extension. the dataset for experiments of our method is the standard dataset of SemEval-2017 Task 8. Experiments of our proposed method with respect to competitor methods in rumor detection show that our method outperforms the state of the art methods.
the proceedings contain 9 papers. the special focus in this conference is on Reproducible Research in patternrecognition. the topics include: A Novel pattern-Based Edit Distance for Automatic Log Parsing: Implem...
ISBN:
(纸本)9783031407727
the proceedings contain 9 papers. the special focus in this conference is on Reproducible Research in patternrecognition. the topics include: A Novel pattern-Based Edit Distance for Automatic Log Parsing: Implementation and Reproducibility Notes;companion Paper: Deep Saliency Map Generators for Multispectral Video Classification;on Challenging Aspects of Reproducibility in Deep Anomaly Detection;On the Implementation of Baselines and Lightweight Conditional Model Extrapolation (LIMES) Under Class-Prior Shift;Combining Max-Tree and CNN for Segmentation of Cellular FIB-SEM Images;Automatic Forest Road Extraction from LiDAR Data Using Convolutional Neural Networks;Promoting Reproducibility of Research Results in international Events (Report from the 4th RRPR).
the proceedings contain 13 papers. the special focus in this conference is on Multimodal patternrecognition of Social Signals in Human-Computer-Interaction. the topics include: Bimodal recognition of Cognitive Load B...
ISBN:
(纸本)9783319592589
the proceedings contain 13 papers. the special focus in this conference is on Multimodal patternrecognition of Social Signals in Human-Computer-Interaction. the topics include: Bimodal recognition of Cognitive Load Based on Speech and Physiological Changes;Human Mobility-pattern Discovery and Next-Place Prediction from GPS Data;Fusion Architectures for Multimodal Cognitive Load recognition;Performance Analysis of Gesture recognition Classifiers for Building a Human Robot Interface;On Automatic Question Answering Using Efficient Primal-Dual Models;Hierarchical Bayesian Multiple Kernel Learning Based Feature Fusion for Action recognition;Audio Visual Speech recognition Using Deep Recurrent Neural Networks;Audio-Visual recognition of Pain Intensity;the SenseEmotion Database: A Multimodal Database for the Development and Systematic Validation of an Automatic Painand Emotion-recognition System;Photometric Stereo for 3D Face Reconstruction Using Non Linear Illumination Models and Recursively Measured Action Units.
this paper is mainly research on the power equipment of visible light spectrum recognition model. the main contents of the research include constructing experimental evaluation of image acquisition standard operating ...
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ISBN:
(纸本)9781450364089
this paper is mainly research on the power equipment of visible light spectrum recognition model. the main contents of the research include constructing experimental evaluation of image acquisition standard operating system, establishing multi-spectral sample library for power equipment, studying HDFS mode based image data storage and management technology, constructing spectral testing technology data centre service framework for power equipment, typical equipment image recognition and analysis algorithm for power network, etc. through the study of these technologies, we aim to achieve the identification of electrical equipment.
In this paper, we applied a Temporal patternrecognition Networks[1] to jigsaw puzzle solving. Contours of pieces are treated as temporal patterns using a φ -s transformation. As a result, the networks realized both ...
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ISBN:
(纸本)0780324625
In this paper, we applied a Temporal patternrecognition Networks[1] to jigsaw puzzle solving. Contours of pieces are treated as temporal patterns using a φ -s transformation. As a result, the networks realized both whole object shape recognition and local shape matching of bordering pieces necessary for jigsaw puzzle solving.
In this paper, a technique for extracting the distortion parameters in filled-informs is presented the technique determines the transformations that is required to convert a filled-in form to match a known master and ...
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ISBN:
(纸本)0818678984;0818678992
In this paper, a technique for extracting the distortion parameters in filled-informs is presented the technique determines the transformations that is required to convert a filled-in form to match a known master and then extracts filled-in information, the method involves determining corresponding lines and key points between the master and the filled-in form and using the correspondence to determine the appropriate transformation. the correspondence problem is solved using results from affine geometry.
this paper describes the Knowledge-based Adaptive recognition System for Drawings (KARD), using a computer and an optical scanner, and its application to chemical structural formula. KARD is designed as a test-bed sys...
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For many biomedical modelling tasks a number of different types of data may influence predictions made by the model. Ail established approach to pursuing supervised learning with multiple types of data, is to encode t...
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ISBN:
(纸本)9783642040306
For many biomedical modelling tasks a number of different types of data may influence predictions made by the model. Ail established approach to pursuing supervised learning with multiple types of data, is to encode these different types of data into separate kernels and use multiple kernel learning. In this paper we propose a, simple iterative approach to multiple kernel learning (MKL), focusing on multi-class classification. this approach uses a block L-1-regularization term leading to a jointly convex formulation. It solves a standard multi-class classification problem for a single kernel, and then updates the kernel combinatorial coefficients based oil mixed RKHS norms. As opposed to other MKL approaches, our iterative approach delivers a largely ignored message that MKL does not require sophisticated optimization methods while keeping competitive training times and accuracy across a variety of problems. We show that the proposed method outperforms state-of-the-art results oil all important protein fold prediction dataset and gives competitive performance on a protein subcellular localization task.
We investigate a knowledge model for our previously proposed approach to object recognition based on low level pattern features. this knowledge includes rules which can deal with situations in which an object may be o...
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ISBN:
(纸本)0780324625
We investigate a knowledge model for our previously proposed approach to object recognition based on low level pattern features. this knowledge includes rules which can deal with situations in which an object may be occluded. the approach is based on fuzzy logic techniques, appropriate when approximate recognition results are adequate. the concept of pattern detectors is also discussed. the approach is illustrated by examples of results for images of office scenes.
We investigate a knowledge model for our previously proposed approach to object recognition based on low level pattern features. this knowledge includes rules which can deal with situations in which an object may be o...
详细信息
ISBN:
(纸本)0780324625
We investigate a knowledge model for our previously proposed approach to object recognition based on low level pattern features. this knowledge includes rules which can deal with situations in which an object may be occluded. the approach is based on fuzzy logic techniques, appropriate when approximate recognition results are adequate. the concept of pattern detectors is also discussed. the approach is illustrated by examples of results for images of office scenes.
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