ML Anthology

High-Speed Airborne Particle Monitoring Using Artificial Neural Networks

Alistair Ferguson, Theo Sabisch, Paul Kaye, Laurence C. Dixon, Hamid Bolouri
NeurIPS 1995 pp. 980-986
/neurips/1995/ferguson1995neurips-highspeed/

Abstract

Current environmental monitoring systems assume particles to be spherical, and do not attempt to classify them. A laser-based sys(cid:173) tem developed at the University of Hertfordshire aims at classify(cid:173) ing airborne particles through the generation of two-dimensional scattering profiles. The pedormances of template matching, and two types of neural network (HyperNet and semi-linear units) are compared for image classification. The neural network approach is shown to be capable of comparable recognition pedormance, while offering a number of advantages over template matching.

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Text

Ferguson et al. "High-Speed Airborne Particle Monitoring Using Artificial Neural Networks." Neural Information Processing Systems, 1995.

Markdown

[Ferguson et al. "High-Speed Airborne Particle Monitoring Using Artificial Neural Networks." Neural Information Processing Systems, 1995.](https://mlanthology.org/neurips/1995/ferguson1995neurips-highspeed/)

BibTeX

@inproceedings{ferguson1995neurips-highspeed,
  title     = {{High-Speed Airborne Particle Monitoring Using Artificial Neural Networks}},
  author    = {Ferguson, Alistair and Sabisch, Theo and Kaye, Paul and Dixon, Laurence C. and Bolouri, Hamid},
  booktitle = {Neural Information Processing Systems},
  year      = {1995},
  pages     = {980-986},
  url       = {https://mlanthology.org/neurips/1995/ferguson1995neurips-highspeed/}
}