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TECHNOLOGY KEYWORDS Code Description ELECTRONICS IT AND TELECOMMS Electronics

TECHNOLOGY KEYWORDS Code Description ELECTRONICS IT AND TELECOMMS Electronics

  • marina-yarberry
  • 8 Slides

separation sorting filtering 002002013 Moulding i...

Comparison of Jaccard Dice Cosine Similarity Coefficient To Find Best Fitness V

Comparison of Jaccard Dice Cosine Similarity Coefficient To Find Best Fitness V

  • celsa-spraggs
  • 4 Slides

KNM UniversityNewai Rajasthan India Dr Vivek Jagl...

Keyword Generation for Search Engine Advertising using Semantic Similarity betwe

Keyword Generation for Search Engine Advertising using Semantic Similarity betwe

  • yoshiko-marsland
  • 6 Slides

com ABSTRACT An important problem in search engine...

Whats in a Name Persuasion Perhaps GARNER NAME SIMILARITY AND PERSUASION Randy G

Whats in a Name Persuasion Perhaps GARNER NAME SIMILARITY AND PERSUASION Randy G

  • stefany-barnette
  • 11 Slides

Some participants received a scenario in which th...

AL ar ge S cale Evaluation of Acoustic and Subjective Music Similarity Measures

AL ar ge S cale Evaluation of Acoustic and Subjective Music Similarity Measures

  • danika-pritchard
  • 7 Slides

SA alb63columbiaedu Be th Logan HP Labs One Cambri...

A Primitive Operator for Similarity Joins in Data Cleaning Surajit Chaudhuri Venkatesh Ganti Raghav Kaushik Microsoft Research surajitcvgantiskaushi microsoft

A Primitive Operator for Similarity Joins in Data Cleaning Surajit Chaudhuri Venkatesh Ganti Raghav Kaushik Microsoft Research surajitcvgantiskaushi microsoft

  • giovanna-bartolotta
  • 12 Slides

com Abstract Data cleaning based on similarities i...

Guided Image Filtering Kaiming He Jian Sun and Xiaoou Tang Department of Information Engineering The Chinese University of Hong Kong Microsoft Research Asia Shenzhen Institutes of Advanced Technolog

Guided Image Filtering Kaiming He Jian Sun and Xiaoou Tang Department of Information Engineering The Chinese University of Hong Kong Microsoft Research Asia Shenzhen Institutes of Advanced Technolog

  • test
  • 14 Slides

In this paper we propose a novel type of explicit...

A Keyword Sense Disambiguation Based Approach for Noise Filtering in Twitter Motivation With growing popularity of streaming social media platforms such as Twitter for news reporting locating timely a

A Keyword Sense Disambiguation Based Approach for Noise Filtering in Twitter Motivation With growing popularity of streaming social media platforms such as Twitter for news reporting locating timely a

  • tatyana-admore
  • 1 Slides

Heravi This project has been funded by SFI grant ...

Laws of Attraction From Perceived Forces to Conceptual Similarity Caroline Ziemkiewicz Member IEEE Robert Kosara Member IEEE Abstract Many of the pressing questions in information visualization deal

Laws of Attraction From Perceived Forces to Conceptual Similarity Caroline Ziemkiewicz Member IEEE Robert Kosara Member IEEE Abstract Many of the pressing questions in information visualization deal

  • danika-pritchard
  • 8 Slides

Previous research has suggested that people see p...

JOURNAL OF EXPERIMENTAL SOCIAL PSYCHOLOGY Exposure Effects in Person Perception Familiarity Similarity and Attraction RICHARD L

JOURNAL OF EXPERIMENTAL SOCIAL PSYCHOLOGY Exposure Effects in Person Perception Familiarity Similarity and Attraction RICHARD L

  • phoebe-click
  • 21 Slides

MORELAND University of Pittsburgh AND ROBERT B ZA...

COMBINE CORNE AN EDG DETECTO Chri Harri Mik Stephen Plesse Researc Rok Manor Unite Kingdo Th Plesse Compan pic Consistency of image edge filtering is of prime importance for D interpretation of ima

COMBINE CORNE AN EDG DETECTO Chri Harri Mik Stephen Plesse Researc Rok Manor Unite Kingdo Th Plesse Compan pic Consistency of image edge filtering is of prime importance for D interpretation of ima

  • luanne-stotts
  • 6 Slides

To cater for image regions containing texture and...

Lear ning isual Similarity Measur es or Comparing Ne er Seen Objects Eric No ak INRIA INPG Bertin echnologies Louis Armand Aix en Pro ence France eric

Lear ning isual Similarity Measur es or Comparing Ne er Seen Objects Eric No ak INRIA INPG Bertin echnologies Louis Armand Aix en Pro ence France eric

  • yoshiko-marsland
  • 8 Slides

nowakinrialpesfr Fr ed eric Jurie LEAR Group CNRS ...

Fast Bilateral Filtering for the Display of HighDynamicRange Images Fr edo Durand and Julie Dorsey Laboratory for Computer Science Massachusetts Institute of Technology Abstract We present a new techn

Fast Bilateral Filtering for the Display of HighDynamicRange Images Fr edo Durand and Julie Dorsey Laboratory for Computer Science Massachusetts Institute of Technology Abstract We present a new techn

  • liane-varnes
  • 10 Slides

It is based on a twoscale decomposition of the im...

COMBINE CORNE AN EDG DETECTO Chri Harri Mik Stephen Plesse Researc Rok Manor Unite Kingdo Th Plesse Compan pic Consistency of image edge filtering is of prime importance for D interpretation of ima

COMBINE CORNE AN EDG DETECTO Chri Harri Mik Stephen Plesse Researc Rok Manor Unite Kingdo Th Plesse Compan pic Consistency of image edge filtering is of prime importance for D interpretation of ima

  • tatiana-dople
  • 6 Slides

To cater for image regions containing texture and...

The Wisdom of the Few A Collaborative Filtering Approach Based on Expert Opinion s from the Web Xavier Amatriain Telefonica Research Via Augusta Barcelona Spain xartid

The Wisdom of the Few A Collaborative Filtering Approach Based on Expert Opinion s from the Web Xavier Amatriain Telefonica Research Via Augusta Barcelona Spain xartid

  • min-jolicoeur
  • 9 Slides

es Neal Lathia Dept of Computer Science University...

Google News Personalization Scalable Online Collaborative Filtering Abhinandan Das Google Inc

Google News Personalization Scalable Online Collaborative Filtering Abhinandan Das Google Inc

  • cheryl-pisano
  • 10 Slides

1600 Amphitheatre Pkwy Mountain View CA 94043 abh...

Restricted Boltzmann Mac hines for Collab orativ Filtering Ruslan Salakh utdino rsalakhucs

Restricted Boltzmann Mac hines for Collab orativ Filtering Ruslan Salakh utdino rsalakhucs

  • mitsue-stanley
  • 8 Slides

tor ontoedu Andriy Mnih amnihcstor ontoedu Geo5735...

Explaining Collaborative Filtering Recommendations ABSTRACT Keywords INTRODUCTION SOURCES OF ERROR ModelProcess Errors Data Errors EXPLANATIONS RESEARCH QUESTIONS What models and techniques are eff

Explaining Collaborative Filtering Recommendations ABSTRACT Keywords INTRODUCTION SOURCES OF ERROR ModelProcess Errors Data Errors EXPLANATIONS RESEARCH QUESTIONS What models and techniques are eff

  • karlyn-bohler
  • 10 Slides

25 129 2 77 519 116 3 78 509 122 4 78 497 129 5 77...

Detecting and Measuring Similarity in Code Clones Randy Smith and Susan Horwitz Department of Computer Sciences University of Wisconsin Madison smithrhorwitz cs

Detecting and Measuring Similarity in Code Clones Randy Smith and Susan Horwitz Department of Computer Sciences University of Wisconsin Madison smithrhorwitz cs

  • trish-goza
  • 7 Slides

wiscedu Abstract Most previous work on codeclone d...

Guided Image Filtering Kaiming He Jian Sun and Xiaoou Tang Department of Information Engineering The Chinese Univer sity of Hong Kong Microsoft Research Asia Shenzhen Institutes of Advanced Technol

Guided Image Filtering Kaiming He Jian Sun and Xiaoou Tang Department of Information Engineering The Chinese Univer sity of Hong Kong Microsoft Research Asia Shenzhen Institutes of Advanced Technol

  • briana-ranney
  • 14 Slides

In this paper we propose a novel type of explicit...

Any signal processing such as amplification sampling filtering noise to a measurement

Any signal processing such as amplification sampling filtering noise to a measurement

  • marina-yarberry
  • 11 Slides

Any signal processing such as amplification sampl...

Jamie Ludwig Satellite Digital Image Analysis Portland State University Filtering Convolution Matrix Color values kernel Convolution filtering is used to modify the spatial frequency characteristic

Jamie Ludwig Satellite Digital Image Analysis Portland State University Filtering Convolution Matrix Color values kernel Convolution filtering is used to modify the spatial frequency characteristic

  • pamella-moone
  • 8 Slides

Convolution is a general purpos e filter effect f...

Video Filtering Considerations for Media Processors By David Katz and Rick Gentile Blackfin Applications Group Analog Devices Inc

Video Filtering Considerations for Media Processors By David Katz and Rick Gentile Blackfin Applications Group Analog Devices Inc

  • olivia-moreira
  • 6 Slides

Until recently designers needing to perform vi de...

Comparison of Unscented and Extended Kalman Filtering for Estimating Quaternion Motion Joseph J

Comparison of Unscented and Extended Kalman Filtering for Estimating Quaternion Motion Joseph J

  • sherrill-nordquist
  • 6 Slides

LaV iola Jr Bro wn Uni ersity echnology Center fo...

Robust Extended Kalman Filtering in Hybrid Positioning Applications Tommi PER AL A and Robert PICH Tampere University of Technology Finland Email tommi

Robust Extended Kalman Filtering in Hybrid Positioning Applications Tommi PER AL A and Robert PICH Tampere University of Technology Finland Email tommi

  • conchita-marotz
  • 9 Slides

perala robertpichetut Abstract The Kalman 64257lt...

Sparse Filtering Jiquan Ngiam Pang Wei Koh Zhenghao Chen Sonia Bhaskar Andrew Y

Sparse Filtering Jiquan Ngiam Pang Wei Koh Zhenghao Chen Sonia Bhaskar Andrew Y

  • trish-goza
  • 9 Slides

Ng Computer Science Department Stanford Universit...

Datadriven Visual Similarity for Crossdomain Image Matching Abhinav Shrivastava Carnegie Mellon University Tomasz Malisiewicz MIT Abhinav Gupta Carnegie Mellon University Alexei A

Datadriven Visual Similarity for Crossdomain Image Matching Abhinav Shrivastava Carnegie Mellon University Tomasz Malisiewicz MIT Abhinav Gupta Carnegie Mellon University Alexei A

  • mitsue-stanley
  • 9 Slides

Efros Carnegie Mellon University Figure 1 In this...

Collaborative Filtering forI mplicit Feedback Datasets Yifan Hu ATT Labs Research Florham Park NJ Yehuda Koren Yahoo Research Haifa Israel Chris Volinsky ATT Labs Research Florham Park NJ Abstra

Collaborative Filtering forI mplicit Feedback Datasets Yifan Hu ATT Labs Research Florham Park NJ Yehuda Koren Yahoo Research Haifa Israel Chris Volinsky ATT Labs Research Florham Park NJ Abstra

  • alida-meadow
  • 10 Slides

These systems pas sively track different sorts of...

Constant Time Weighted Median Filtering for Stereo Matching and Beyond Ziyang Ma Kaiming He Yichen Wei Jian Sun Enhua Wu University of Chinese Academy of Sciences State Key Laboratory of Computer Sc

Constant Time Weighted Median Filtering for Stereo Matching and Beyond Ziyang Ma Kaiming He Yichen Wei Jian Sun Enhua Wu University of Chinese Academy of Sciences State Key Laboratory of Computer Sc

  • min-jolicoeur
  • 8 Slides

Little attention has been seriously paid to the d...

Learning Hierarchical Similarity Metrics Nakul Verma UC San Diego navermacs

Learning Hierarchical Similarity Metrics Nakul Verma UC San Diego navermacs

  • calandra-battersby
  • 8 Slides

ucsdedu Dhruv Mahajan Sundararajan Sellamanickam Y...

EE Lecture Wiener Filtering In this lecture we will tak dif ferent vie of ltering

EE Lecture Wiener Filtering In this lecture we will tak dif ferent vie of ltering

  • ellena-manuel
  • 11 Slides

Pre viously we ha depended on fr equencydomain sp...

MODELING RHYTHM SIMILARITY FOR ELECTRONIC DANCE MUSIC Maria Panteli University of Amsterdam Amsterdam Netherlands m

MODELING RHYTHM SIMILARITY FOR ELECTRONIC DANCE MUSIC Maria Panteli University of Amsterdam Amsterdam Netherlands m

  • cheryl-pisano
  • 6 Slides

xpanteligmailcom Niels Bogaards Elephantcandy Amst...

Filtering In discussing Fourier transforms we developed a number of important prop erties among them the convolution property and the modulation property

Filtering In discussing Fourier transforms we developed a number of important prop erties among them the convolution property and the modulation property

  • celsa-spraggs
  • 12 Slides

The convolution property forms the basis for the ...

Similarity Estimation Techniques from Rounding Algorithms Moses S

Similarity Estimation Techniques from Rounding Algorithms Moses S

  • sherrill-nordquist
  • 9 Slides

Charikar Dept of Computer Science Princeton Unive...

Unscented Filtering and Nonlinear Estimation SIMON J

Unscented Filtering and Nonlinear Estimation SIMON J

  • test
  • 22 Slides

JULIER MEMBER IEEE AND JEFFREY K UHLMANN MEMBER...

Noise reduction by filtering is the most commonly used method for improving signaltonoise ratio

Noise reduction by filtering is the most commonly used method for improving signaltonoise ratio

  • faustina-dinatale
  • 4 Slides

The increase in settling time however can be a se...

Learning Finegrained Image Similarity with Deep Ranking Jiang Wang Yang Song Thomas Leung Chuck Rosenberg Jingbin Wang James Philbin Bo Chen Ying Wu Northwestern University Google Inc

Learning Finegrained Image Similarity with Deep Ranking Jiang Wang Yang Song Thomas Leung Chuck Rosenberg Jingbin Wang James Philbin Bo Chen Ying Wu Northwestern University Google Inc

  • stefany-barnette
  • 8 Slides

California Institute of Technology jwa368yingwuee...

Angular Quantizationbased Binary Codes for Fast Similarity Search Yunchao Gong Sanjiv Kumar Vishal Verma Svetlana Lazebnik Google Research New York NY USA Computer Science Department University o

Angular Quantizationbased Binary Codes for Fast Similarity Search Yunchao Gong Sanjiv Kumar Vishal Verma Svetlana Lazebnik Google Research New York NY USA Computer Science Department University o

  • sherrill-nordquist
  • 9 Slides

uncedu sanjivkgooglecom slazebniuiucedu Abstract T...

Eigentaste A Constant Time Collaborative Filtering Algorithm Ken Goldberg and Theresa Roeder and Dhruv Gupta and Chris Perkins IEOR and EECS Departments University of California Berkeley August Abst

Eigentaste A Constant Time Collaborative Filtering Algorithm Ken Goldberg and Theresa Roeder and Dhruv Gupta and Chris Perkins IEOR and EECS Departments University of California Berkeley August Abst

  • tatiana-dople
  • 11 Slides

PCA facilitates dimensionality reduction for of64...

Adjacent Channel Interference Effects in OFDM Systems with Imperfect AntiAliasing Filtering Florian Klingler and Henrik Schulze Robert Bosch GmbH Corporate Research P

Adjacent Channel Interference Effects in OFDM Systems with Imperfect AntiAliasing Filtering Florian Klingler and Henrik Schulze Robert Bosch GmbH Corporate Research P

  • olivia-moreira
  • 5 Slides

O Box 77 77 77 D31132 Hildesheim Germany 64258oria...

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