A method for image classification using low-precision analog computing arrays

@inproceedings{Fieres2006AMF,
  title={A method for image classification using low-precision analog computing arrays},
  author={Johannes Fieres},
  year={2006}
}
Computing with analog micro electronics can offer several advantages over standard digital technology, most notably: Low space and power consumption and massive parallelization. On the other hand, analog computation lacks the exactness of digital calculations due to inevitable device variations introduced during the chip production, but also due to electric noise in the analog signals. Artificial neural networks are well suited for parallel analog implementations, first, because of their… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-10 of 58 references

A mixed-mode analog neural network using current-steering synapses

J. Schemmel, S. Hohmann, K. Meier, F. Schurmann
Analog Integrated Circuits and Signal Processing • 2004
View 7 Excerpts
Highly Influenced

Evaluation of convolutional neural networks for visual recognition

IEEE Trans. Neural Networks • 1998
View 7 Excerpts
Highly Influenced

Learning Recognition and Segmentation Using the Cresceptron

International Journal of Computer Vision • 1997
View 5 Excerpts
Highly Influenced

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