Clustering Learning for Robotic Vision
Abstract
We present the clustering learning technique applied to multi-layer feedforward deep neural networks. We show that this unsupervised learning technique can compute network filters with only a few minutes and a much reduced set of parameters. The goal of this paper is to promote the technique for general-purpose robotic vision systems. We report its use in static image datasets and object tracking datasets. We show that networks trained with clustering learning can outperform large networks trained for many hours on complex datasets.
Cite
Text
Culurciello et al. "Clustering Learning for Robotic Vision." International Conference on Learning Representations, 2013.Markdown
[Culurciello et al. "Clustering Learning for Robotic Vision." International Conference on Learning Representations, 2013.](https://mlanthology.org/iclr/2013/culurciello2013iclr-clustering/)BibTeX
@inproceedings{culurciello2013iclr-clustering,
title = {{Clustering Learning for Robotic Vision}},
author = {Culurciello, Eugenio and Bates, Jordan and Dundar, Aysegul and Pérez-Carrasco, José Antonio and Farabet, Clément},
booktitle = {International Conference on Learning Representations},
year = {2013},
url = {https://mlanthology.org/iclr/2013/culurciello2013iclr-clustering/}
}