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» Feature selection for grasp recognition from optical markers
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IROS
2007
IEEE
134views Robotics» more  IROS 2007»
13 years 11 months ago
Feature selection for grasp recognition from optical markers
Abstract— Although the human hand is a complex biomechanical system, only a small set of features may be necessary for observation learning of functional grasp classes. We explor...
Lillian Y. Chang, Nancy S. Pollard, Tom M. Mitchel...
PRL
2000
148views more  PRL 2000»
13 years 5 months ago
One-dimensional representation of two-dimensional information for HMM based handwriting recognition
: In this study, we introduce a set of one-dimensional features to represent two dimensional shape information for HMM (Hidden Markov Model) based handwritten optical character rec...
Nafiz Arica, Fatos T. Yarman-Vural
BMCBI
2004
133views more  BMCBI 2004»
13 years 5 months ago
Artificial neural network approach for selection of susceptible single nucleotide polymorphisms and construction of prediction m
Background: Screening of various gene markers such as single nucleotide polymorphism (SNP) and correlation between these markers and development of multifactorial disease have pre...
Yasuyuki Tomita, Shuta Tomida, Yuko Hasegawa, Yoic...
ICRA
1994
IEEE
89views Robotics» more  ICRA 1994»
13 years 9 months ago
Computation of Shape Through Controlled Active Exploration
Accurate knowledge of depth continues to be of critical importance in robotic systems. Without accurate depth knowledge, tasks such as inspection, tracking, grasping, and collisio...
Christopher E. Smith, Nikolaos Papanikolopoulos
IROS
2006
IEEE
127views Robotics» more  IROS 2006»
13 years 11 months ago
Learning Predictive Features in Affordance based Robotic Perception Systems
This work is about the relevance of Gibson’s concept of affordances [1] for visual perception in interactive and autonomous robotic systems. In extension to existing functional ...
Gerald Fritz, Lucas Paletta, Ralph Breithaupt, Eri...