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SIGGRAPH
1999
ACM
15 years 4 months ago
Creating Generative Models from Range Images
We describe a new approach for creating concise high-level generative models from range images or other approximate representations of real objects. Using data from a variety of a...
Ravi Ramamoorthi, James Arvo
KES
1998
Springer
15 years 4 months ago
An acquisition of the relation between vision and action using self-organizing map and reinforcement learning
An agent must acquire internal representation appropriate for its task, environment, sensors. As a learning algorithm, reinforcement learning is often utilized to acquire the rela...
Kazunori Terada, Hideaki Takeda, Toyoaki Nishida
JMLR
2012
13 years 2 months ago
Deep Boltzmann Machines as Feed-Forward Hierarchies
The deep Boltzmann machine is a powerful model that extracts the hierarchical structure of observed data. While inference is typically slow due to its undirected nature, we argue ...
Grégoire Montavon, Mikio L. Braun, Klaus-Ro...
ICIP
2009
IEEE
16 years 26 days ago
Physics-based Illuminant Color Estimation As An Image Semantics Clue
Most algorithms for extracting illuminant chromaticity from arbitrary images, such as the images found on the web, are based on machine learning techniques. We will show how a phy...
NIPS
2003
15 years 1 months ago
A Holistic Approach to Compositional Semantics: A Connectionist Model and Robot Experiments
We present a novel connectionist model for acquiring the semantics of a simple language through the behavioral experiences of a real robot. We focus on the “compositionality” ...
Yuuya Sugita, Jun Tani