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12th international conference on Intelligent computing (ICIC)

作者： Baklanova, Olga E. Baklanov, Mikhail A. D Serikbayev East Kazakhstan State Tech Univ Ust Kamenogorsk Kazakhstan Tomsk State Univ Tomsk Russia

ISBN: (纸本)9783319422947;9783319422930

this paper describes an algorithm for automatic segmentation of color images of various ore types, using the methods of morphological and cluster analysis. there are some examples illustrating the usage of the algorithm to solve mineral recognition problems. the effectiveness of the proposed method lies in the area of automatic objects of interest identification inside the image, tuning the parameters of the amount allocated to the segments. this paper contains short description of morphological and cluster analysis algorithms for the mineral recognition in the mining industry.

关键词： pattern recognition Segmentation of color images Cluster analysis Morphological analysis Mineral rocks Mining industry

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Texture of Activities: Exploiting Local Binary patterns for Accelerometer Data Analysis 12

Texture of Activities: Exploiting Local Binary Patterns for ...

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12th international conference on Signal-Image Technology and Internet-Based Systems (SITIS)

作者： Asuroglu, Tunc Acici, Koray Erdas, Cagatay Berke Ogul, Hasan Baskent Univ Dept Comp Engn Ankara Turkey

ISBN: (纸本)9781509056989

recognition of activities through wearable sensors such as accelerometers is a recent challenge in pervasive and ubiquitous computing. the problem is often considered as a classification task where a set of descriptive features are extracted from input signal to feed a machine learning classifier. A major issue ignored so far in these studies is the incorporation of locally embedded features that could indeed be informative in describing the main activity performed by the individual being experimented. To close this gap, we offer here adapting Local Binary pattern (LBP) approach, which is frequently used in identifying textures in images, in one-dimensional space of accelerometer data. To this end, we exploit the histogram of LPB found in each axes of input accelerometer signal as a feature set to feed a k-Nearest Neighbor classifier. the experiments on a benchmark dataset have shown that the proposed method can outperform some previous methods.

关键词： activity recognition accerelometer data wearable sensor classification local binary pattern

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A Picture of the Growing ICER Community 16

A Picture of the Growing ICER Community

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12th ACM Annual conference on international computing Education Research (ICER)

作者： Simon Univ Newcastle Callaghan NSW 2308 Australia

ISBN: (纸本)9781450344494

this bibliometric study examines the authorship of the papers presented at ICER since the conference began in 2005. It finds that the pattern of authorship complies well with Lotka's law, an accepted model of author distribution within a discipline. ICER's most prolific authors are identified and their contributions quantified, along with measures of the collaborations between authors. New authors are found to be joining the community at a steady rate, some beginning as co-authors with established community members and some joining alone or with other new authors. the analysis extends to the contributions from different countries. the conclusion is that the community of ICER authors is truly international, has a solid core around which excellent growth is evident, displays strong collaboration, and has at least one of the characteristics of a full-fledged discipline.

关键词： computing education research author productivity bibliometrics

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Fast and Parallel Summed Area Table for Fabric Defect Detection

Fast and Parallel Summed Area Table for Fabric Defect Detect...

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11th international conference on Natural Computation (ICNC) / 12th international conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Ragab, Khaled King Faisal Univ Coll Comp Sci & Informat Technol Al Hufuf Saudi Arabia

Automating fabric defect detection has a significant role in fabric industries. However, the existing fabric defect detection algorithms lack the real-time performance that is required in real applications due to their high demanding computation. To ensure real time, high accuracy and reliable fabric defect detection this paper developed a fast and parallel normalized cross-correlation algorithm based on summed-area table technique called PFDD-SAT. To meet real-time requirements, extensive use of the NVIDIA CUDA framework for Graphical Processing Unit (GPU) computing is made. the detailed implementation steps of the PFDD-SAT are illustrated in this paper. Several experiments have been carried out to evaluate the detection time and accuracy and then the robustness to illumination and Gaussian noises. the results show that the PFDD-SAT has robustness to noise and speeds the defect detection process more than 200 times than normal required time and that greatly met the needs for real-time automatic fabric defect detection.

关键词： Parallel computing fabric defect detection GPU normalized-cross correlation summed area table

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12th international Symposium on Visual computing, ISVC 2016

12th International Symposium on Visual Computing, ISVC 2016

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12th international Symposium on Visual computing, ISVC 2016

ISBN: (纸本)9783319508344

the proceedings contain 77 papers. the special focus in this conference is on Computational Bioimaging, Computer Graphics, Motion, Tracking, Segmentation, pattern recognition, Visualization, 3D Mapping, Modeling, Surface Reconstruction, Visual Perception and Robotic Systems. the topics include: Similarity metric learning for 2D to 3D registration of brain vasculature;automatic optic disk segmentation in presence of disk blurring;tensor voting extraction of vessel centerlines from cerebral angiograms;stacked autoencoders for medical image search;an interactive exploration tool for cancer biomarker cutpoint optimization;adding turbulence based on low-resolution cascade ratios;creating feasible reflectance data for synthetic optical flow datasets;automatic web page coloring;automatic content-aware non-photorealistic rendering of images;detecting tracking failures from correlation response maps;camera motion estimation with known vertical direction in unstructured environments;reliability-based local features aggregation for image segmentation;image enhancement by volume limitation in binary tomography;optimizing intersection-over-union in deep neural networks for image segmentation;a mobile recognition system for analog energy meter scanning;towards landmine detection using ubiquitous satellite imaging;robustness of rotation invariant descriptors for texture classification;pollen grain recognition using deep learning;complementary keypoint descriptors;interpolation-based extraction of representative isosurfaces;spatiotemporal LOD-Blending for artifact reduction in multi-resolution volume rendering;visual analytics using graph sampling and summarization on multitouch displays;an efficient algorithm for feature-based 3D point cloud correspondence search;combining visual tracking and person detection for long term tracking on a UAV and change detection and object recognition using aerial robots.

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12th IFIP WG 12.5 international conference and Workshops on Artificial Intelligence Applications and Innovations, AIAI 2016

12th IFIP WG 12.5 International Conference and Workshops on ...

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12th IFIP WG 12.5 international conference and Workshops on Artificial Intelligence Applications and Innovations, AIAI 2016

ISBN: (纸本)9783319449432

the proceedings contain 62 papers. the special focus in this conference is on Medical Artificial Intelligence Modeling, Classification - pattern recognition, Ontology-Web and Social Media AI Modeling, Environmental AI Modeling, Machine Learning-Learning, Optimization-SVM, Agents-Robotics-Control, Artificial Neural Network Modeling and New Methods and Tools for Big Data wokshop. the topics include: A cumulative training approach to schistosomiasis vector density prediction;mobile and evolving tool to predict colorectal cancer survivability;machine learning preprocessing method for suicide prediction;increasing diversity in random forests using naive bayes;identifying asperity patterns via machine learning algorithms;combining prototype selection with local boosting;modeling economic open data;web image indexing using wice and a learning-free language model;an intelligent internet search assistant based on the random neural network;deep neural networks for web page information extraction;environmental impact on predicting olive fruit fly population using trap measurements;a hybrid soft computing approach producing robust forest fire risk indices;applying artificial neural networks to short-term pm2.5 forecasting modeling;convolutive audio source separation using robust ica and reduced likelihood ratio jump;use of flight simulators in analyzing pilot behavior;active learning algorithms for multi-label data;design of an advanced smart forum for tesys e-learning platform;efficient support vector machine classification using prototype selection and generation;genetic search of pickup and delivery problem solutions for self-driving taxi routing and introducing chemotaxis to a mobile robot.

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proceedings - 2015 IEEE 12th international conference on Ubiquitous Intelligence and computing, 2015 IEEE 12th international conference on Advanced and Trusted computing, 2015 IEEE 15th international conference on Scalable computing and Communications, 2015 IEEE international conference on Cloud and Big Data computing, 2015 IEEE international conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015

Proceedings - 2015 IEEE 12th International Conference on Ubi...

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proceedings - 2015 IEEE 12th international conference on Ubiquitous Intelligence and computing, 2015 IEEE 12th international conference on Advanced and Trusted computing, 2015 IEEE 15th international conference on Scalable computing and Communications, 2015 IEEE international conference on Cloud and Big Data computing, 2015 IEEE international conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015

ISBN: (纸本)9781467372114

the proceedings contain 314 papers. the topics discussed include: recognizing gait pattern of Parkinson's disease patients based on fine-grained movement function features;SAPM: self-adjusting pipelining mechanism for efficient bulk data dissemination in smart homes;WSelector: a multi-scenario and multi-view worker selection framework for crowd-sensing;CrowdPic: a multi-coverage picture collection framework for mobile crowd photographing;an acoustic traffic monitoring system: design and implementation;an interpretable orientation and placement invariant approach for smartphone based activity recognition;characterising and predicting urban mobility dynamics by mining bike sharing system data;underground magnetic localization method and optimization based on simulated annealing algorithm;an adaptive demodulation structure for UHF RFID readers based on the phase of input signal;intelligently creating contextual tutorials for GUI applications;HyCPK: securing identity authentication in ubiquitous computing;context-aware trust-based management of vehicular ad-hoc networks (VANETs);and BWMesh: a multi-hop connectivity framework on Android for proximity service.

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Fast and Parallel Summed Area Table for Fabric Defect Detection

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international JOURNAL OF pattern recognition AND ARTIFICIAL INTELLIGENCE 2016年第9期30卷 1660004-1660004页

作者： Ragab, Khaled King Faisal Univ Coll Comp Sci & Informat Technol Al Hufuf Saudi Arabia

关键词： Parallel computing fabric defect detection GPU normalized-cross correlation summed area table

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Audio Recorder Forensic Identification in 21 Audio Recorders 3

Audio Recorder Forensic Identification in 21 Audio Recorders

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3rd IEEE international conference on Progress in Informatcs and computing (IEEE PIC)

作者： Zeng, Jinhua Shi, Shaopei Yang, Xu Li, Yan Lu, Qimeng Qiu, Xiulian Zhu, Huaping Minist Justice Inst Forens Sci Shanghai 200063 Peoples R China Tongji Univ Coll Civil Engn Shanghai Peoples R China

ISBN: (纸本)9781467390880

Audio recorder forensic identification is to determine originating devices of questioned audio recordings. In this paper, statistical features both in time and frequency domains were studied and were used to represent and encode device-related information. Statistical techniques in fields of machine learning and pattern recognition were utilized to classify computed features into each originating audio recorder. More specifically, features of sampling histogram and spectral mean were extracted from near-silence segments of digital recordings which were recorded by using 21 audio recorders. A support vector machine classifier was used to learn device-related feature patterns upon one half of the complete set of audio samples, and then was evaluated by using the rest of data. the experimental results show a high accuracy of up to 96.72% in the correct classification of the 21 audio recorders. Our paper was the first study which was to study and evaluate the performances of different features for device-related information encoding in a relatively big audio recorder database. the proposed method would offer a practical guide for forensic identification of audio recorders.

关键词： Audio recorder forensic identification pattern classification Sampling histogram Spectral mean Statistical feature

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Target-based rhythmic pattern generation and variation with genetic algorithms 12

Target-based rhythmic pattern generation and variation with ...

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12th international conference on Sound and Music computing, SMC 2015

作者： Nuanáin, Cárthach Ó. Herrera, Perfecto Jordà, Sergi Music Technology Group Universitat Pompeu Fabra Barcelona Spain

ISBN: (纸本)9780992746629

Composing drum patterns and musically developing them through repetition and variation is a typical task in electronic music production. We propose a system that, given an input pattern, automatically creates related patterns using a genetic algorithm. Two distance measures (the Hamming distance and directed-swap distance) that relate to rhythmic similarity are shown to derive usable fitness functions for the algorithm. A software instrument in the Max for Live environment presents how this can be used in real musical applications. Finally, a user survey was carried out to examine and compare the effectiveness of the fitness metrics in determining rhythmic similarity as well as the usefulness of the instrument for musical creation. © 2015 Cárthach Ó Nuanáin,.

关键词： Genetic algorithms

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