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Richard Howard
Researcher at Rutgers University
Publications - 225
Citations - 22069
Richard Howard is an academic researcher from Rutgers University. The author has contributed to research in topics: Artificial neural network & Josephson effect. The author has an hindex of 47, co-authored 222 publications receiving 18566 citations. Previous affiliations of Richard Howard include Bell Labs & AT&T.
Papers
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Journal ArticleDOI
Backpropagation applied to handwritten zip code recognition
Yann LeCun,Bernhard E. Boser,John S. Denker,D. Henderson,Richard Howard,W. Hubbard,Lawrence D. Jackel +6 more
TL;DR: This paper demonstrates how constraints from the task domain can be integrated into a backpropagation network through the architecture of the network, successfully applied to the recognition of handwritten zip code digits provided by the U.S. Postal Service.
Proceedings Article
Handwritten Digit Recognition with a Back-Propagation Network
Yann LeCun,Bernhard E. Boser,John S. Denker,John S. Denker,D. Henderson,Richard Howard,W. Hubbard,Lawrence D. Jackel +7 more
TL;DR: Minimal preprocessing of the data was required, but architecture of the network was highly constrained and specifically designed for the task, and has 1% error rate and about a 9% reject rate on zipcode digits provided by the U.S. Postal Service.
Journal ArticleDOI
Discrete Resistance Switching in Submicrometer Silicon Inversion Layers: Individual Interface Traps and Low-Frequency ( 1 f ?) Noise
K. S. Ralls,W. J. Skocpol,Lawrence D. Jackel,Richard Howard,Linus A. Fetter,R. W. Epworth,Donald M. Tennant +6 more
TL;DR: In this article, the authors studied resistance fluctuation in submicrometer narrow Si inversion layers over a wide range of temperatures and electron concentrations, caused by the capture and emission of individual electrons at strategically located scatterers (interface traps).
Journal ArticleDOI
Handwritten digit recognition: applications of neural network chips and automatic learning
Y. Le Cun,Lawrence D. Jackel,Bernhard E. Boser,John S. Denker,Hans Peter Graf,Isabelle Guyon,D. Henderson,Richard Howard,W. Hubbard +8 more
TL;DR: Two novel methods for achieving handwritten digit recognition are described, based on a neural network chip that performs line thinning and feature extraction using local template matching and on a digital signal processor that makes extensive use of constrained automatic learning.
Journal ArticleDOI
Heat Capacity Measurements on Small Samples at Low Temperatures
R. Bachmann,F. J. DiSalvo,Theodore H. Geballe,Richard L. Greene,Richard Howard,C. N. King,H. C. Kirsch,K. N. Lee,Robert E. Schwall,H. U. Thomas,R. B. Zubeck +10 more
TL;DR: In this paper, the authors describe a new calorimeter for measuring heat capacity in the range 1-35 K, using a silicon chip bolometer as sample holder, temperature sensor, and sample heater.