Image Recognition in Context: Application to Microscopic Urinalysis
Abstract
We propose a new and efficient technique for incorporating contextual information into object classification. Most of the current techniques face the problem of exponential computation cost. In this paper, we propose a new general framework that incorporates partial context at a linear cost. This technique is applied to microscopic urinalysis image recognition, resulting in a significant improvement of recognition rate over the context free approach. This gain would have been impossible using conventional context incorporation techniques.
Cite
Text
Song et al. "Image Recognition in Context: Application to Microscopic Urinalysis." Neural Information Processing Systems, 1999.Markdown
[Song et al. "Image Recognition in Context: Application to Microscopic Urinalysis." Neural Information Processing Systems, 1999.](https://mlanthology.org/neurips/1999/song1999neurips-image/)BibTeX
@inproceedings{song1999neurips-image,
title = {{Image Recognition in Context: Application to Microscopic Urinalysis}},
author = {Song, Xubo B. and Sill, Joseph and Abu-Mostafa, Yaser S. and Kasdan, Harvey},
booktitle = {Neural Information Processing Systems},
year = {1999},
pages = {963-969},
url = {https://mlanthology.org/neurips/1999/song1999neurips-image/}
}