A Self-Organizing Integrated Segmentation and Recognition Neural Net
Abstract
We present a neural network algorithm that simultaneously performs seg(cid:173) mentation and recognition of input patterns that self-organizes to detect input pattern locations and pattern boundaries. We demonstrate this neu(cid:173) ral network architecture on character recognition using the NIST database and report on results herein. The resulting system simultaneously seg(cid:173) ments and recognizes touching or overlapping characters, broken charac(cid:173) ters, and noisy images with high accuracy.
Cite
Text
Keeler and Rumelhart. "A Self-Organizing Integrated Segmentation and Recognition Neural Net." Neural Information Processing Systems, 1991.Markdown
[Keeler and Rumelhart. "A Self-Organizing Integrated Segmentation and Recognition Neural Net." Neural Information Processing Systems, 1991.](https://mlanthology.org/neurips/1991/keeler1991neurips-selforganizing/)BibTeX
@inproceedings{keeler1991neurips-selforganizing,
title = {{A Self-Organizing Integrated Segmentation and Recognition Neural Net}},
author = {Keeler, Jim and Rumelhart, David E.},
booktitle = {Neural Information Processing Systems},
year = {1991},
pages = {496-503},
url = {https://mlanthology.org/neurips/1991/keeler1991neurips-selforganizing/}
}