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» Object Classification in Visual Surveillance Using Adaboost
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ECCV
2010
Springer
14 years 9 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
TEI
2012
ACM
258views Hardware» more  TEI 2012»
13 years 5 months ago
The HapticTouch toolkit: enabling exploration of haptic interactions
In the real world, touch based interaction relies on haptic feedback (e.g., grasping objects, feeling textures). Unfortunately, such feedback is absent in current tabletop systems...
David Ledo, Miguel A. Nacenta, Nicolai Marquardt, ...
ISBI
2002
IEEE
15 years 10 months ago
Automated determination of protein subcellular locations from 3D fluorescence microscope images
Knowing the subcellular location of a protein is critical to a full understanding of its function, and automated, objective methods for assigning locations are needed as part of t...
Meel Velliste, Robert F. Murphy
TEI
2010
ACM
134views Hardware» more  TEI 2010»
15 years 4 months ago
Tangible lightscapes
Tangible Lightscapes is a research on interfaces mainly based on light and gestures. The aim of my exploration is to design a vocabulary of light behaviours to show people what th...
Alice V. Pintus
ICDM
2006
IEEE
135views Data Mining» more  ICDM 2006»
15 years 3 months ago
SAXually Explicit Images: Finding Unusual Shapes
Among the visual features of multimedia content, shape is of particular interest because humans can often recognize objects solely on the basis of shape. Over the past three decad...
Li Wei, Eamonn J. Keogh, Xiaopeng Xi