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ICCV
2007
IEEE
14 years 9 months ago
Boosting Invariance and Efficiency in Supervised Learning
In this paper we present a novel boosting algorithm for supervised learning that incorporates invariance to data transformations and has high generalization capabilities. While on...
Andrea Vedaldi, Paolo Favaro, Enrico Grisan
ICCV
2003
IEEE
14 years 9 months ago
Learning Pedestrian Models for Silhouette Refinement
We present a model-based method for accurate extraction of pedestrian silhouettes from video sequences. Our approach is based on two assumptions, 1) there is a common appearance t...
L. Lee, Gerald Dalley, Kinh Tieu
IROS
2006
IEEE
126views Robotics» more  IROS 2006»
14 years 1 months ago
A System for Robotic Heart Surgery that Learns to Tie Knots Using Recurrent Neural Networks
Abstract— Tying suture knots is a time-consuming task performed frequently during Minimally Invasive Surgery (MIS). Automating this task could greatly reduce total surgery time f...
Hermann Georg Mayer, Faustino J. Gomez, Daan Wiers...
FLAIRS
2010
13 years 10 months ago
Learning to Identify and Track Imaginary Objects Implied by Gestures
A vision-based machine learner is presented that learns characteristic hand and object movement patterns for using certain objects, and uses this information to recreate the "...
Andreya Piplica, Alexandra Olivier, Allison Petros...
TIP
2008
86views more  TIP 2008»
13 years 7 months ago
Learning the Dynamics and Time-Recursive Boundary Detection of Deformable Objects
We propose a principled framework for recursively segmenting deformable objects across a sequence of frames. We demonstrate the usefulness of this method on left ventricular segmen...
Walter Sun, Müjdat Çetin, Raymond C. C...