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» On the Dimensionality of Face Space
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MVA
2000
172views Computer Vision» more  MVA 2000»
15 years 7 months ago
Partial Face Extraction and Recognition Using Radial Basis Function Networks
work, applies a nonlinear transformation from the input space to the hidden space. The output layer Partial face images, e.g.1 eyes, nose, and ear supplies the response of the netw...
Nan He, Kiminori Sato, Yukitoshi Takahashi
ECIR
2008
Springer
15 years 8 months ago
Filaments of Meaning in Word Space
Word space models, in the sense of vector space models built on distributional data taken from texts, are used to model semantic relations between words. We argue that the high dim...
Jussi Karlgren, Anders Holst, Magnus Sahlgren
SIGMOD
2002
ACM
219views Database» more  SIGMOD 2002»
16 years 6 months ago
Efficient k-NN search on vertically decomposed data
Applications like multimedia retrieval require efficient support for similarity search on large data collections. Yet, nearest neighbor search is a difficult problem in high dimen...
Arjen P. de Vries, Nikos Mamoulis, Niels Nes, Mart...
IJCNN
2006
IEEE
16 years 15 days ago
Bi-directional Modularity to Learn Visual Servoing Tasks
— This paper shows the advantage of using neural network modularity over conventional learning schemes to approximate complex functions. Indeed, it is difficult for artificial ...
Gilles Hermann, Patrice Wira, Jean-Philippe Urban
IJRR
2011
174views more  IJRR 2011»
15 years 1 months ago
Bounding on rough terrain with the LittleDog robot
— In this paper we develop an RRT-based motion planner that achieved bounding in simulation with the LittleDog robot over extremely rough terrain. LittleDog is a quadruped robot ...
Alexander C. Shkolnik, Michael Levashov, Ian R. Ma...