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    CVPR
    2009
    IEEE
    440views Computer Vision» more  CVPR 2009»
    Multiple Instance Feature for Robust Part-based Object Detection
    15 years 3 months ago
    Multiple Instance Feature for Robust Part-based Object Detection
    Download  terpconnect.umd.edu
    Feature misalignment in object detection refers to the phenomenon that features which re up in some positive detection windows do not re up in other pos- itive detection windo...
    Zhe Lin (University of Maryland at College Park), ...
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    AIRWEB
    2008
    Springer
    151views Internet Technology» more  AIRWEB 2008»
    Robust PageRank and locally computable spam detection features
    13 years 10 months ago
    Robust PageRank and locally computable spam detection features
    Download  airweb.cse.lehigh.edu
    Since the link structure of the web is an important element in ranking systems on search engines, web spammers widely use the link structure of the web to increase the rank of the...
    Reid Andersen, Christian Borgs, Jennifer T. Chayes...
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    SAC
    2004
    ACM
    208views Applied Computing» more  SAC 2004»
    Concatenate feature extraction for robust 3D elliptic object localization
    14 years 1 months ago
    Concatenate feature extraction for robust 3D elliptic object localization
    Download  www.people.vcu.edu
    Developing an efficient object localization system for complicated industrial objects is an important, yet difficult robotic task. To tackle this problem, we have developed a syst...
    Yuichi Motai, Akio Kosaka
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    KDD
    2012
    ACM
    207views Data Mining» more  KDD 2012»
    Robust multi-task feature learning
    11 years 10 months ago
    Robust multi-task feature learning
    Download  www.public.asu.edu
    Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning alg...
    Pinghua Gong, Jieping Ye, Changshui Zhang
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    SPLC
    2008
    115views Software Engineering» more  SPLC 2008»
    Filtered Cartesian Flattening: An Approximation Technique for Optimally Selecting Features while Adhering to Resource Constraint
    13 years 9 months ago
    Filtered Cartesian Flattening: An Approximation Technique for Optimally Selecting Features while Adhering to Resource Constraint
    Download  www.dre.vanderbilt.edu
    Software Product-lines (SPLs) use modular software components that can be reconfigured into different variants for different requirements sets. Feature modeling is a common method...
    Jules White, B. Doughtery, Douglas C. Schmidt
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