Real-time signature verification using neural network algorithms to process optically extracted features

1994 ◽  
Author(s):  
Ned F. O'Brien ◽  
Steven C. Gustafson
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Signature Verification ◽  
Network Algorithms ◽  
Time Signature

scholarly journals Real-Time Signature Recognition Using Neural Network

2021 ◽  
Vol 26 (1) ◽  
pp. 159-165
Author(s):  
Ahmed Fadhil ◽  
Mayada Faris ◽  
Ali Al-Saegh ◽  
Mohammad Mohammad
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Signature Recognition ◽  
Time Signature

Developed Incident Detection Algorithm Compared with Neural Network Algorithms

2003 ◽  
Vol 1836 (1) ◽  
pp. 83-92 ◽  
Author(s):  
Hualiang(Harry) Teng ◽  
Yi(Grace) Qi ◽  
David R. Martinelli
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Detection Algorithm ◽  
Incident Detection ◽  
Decision Threshold ◽  
Network Algorithms ◽  
Detection Delay ◽  
The Neural Network ◽  
Before And After ◽  
Neural Network Algorithm

The CUSUM (cumulative sum of log-likelihood ratio) algorithm is an optimization-based algorithm that is attractive for many applications because it can minimize detection delay and can explicitly incorporate the characteristics of processes before and after changes. One such application is freeway incident detection, where field-measurable traffic-flow parameters are used to flag incidents in real time in an expedient and reliable manner. In the presented study, the special characteristics of traffic processes associated with incidents are incorporated into the CUSUM algorithm for freeway incident detection. In the algorithm evaluation, the most recently developed neural networks are compared with an enhanced CUSUM algorithm. The neural network algorithms are systematically evaluated first among themselves, and then the best of them is compared with the CUSUM algorithm. The results demonstrate that the CUSUM incident detection algorithm can perform better than the neural network algorithms. The neural network algorithm may show inferior performance because it cannot adjust its decision threshold in real time.

Cellular Neural Network Algorithms for Real-Time Image Analysis in Plasma Fusion

2009 ◽  
Vol 58 (8) ◽  
pp. 2417-2425 ◽  
Author(s):  
G. Vagliasindi ◽  
A. Murari ◽  
P. Arena ◽  
L. Fortuna ◽  
G. Mazzitelli
Keyword(s):  
Neural Network ◽  
Image Analysis ◽  
Real Time ◽  
Cellular Neural Network ◽  
Network Algorithms ◽  
Plasma Fusion ◽  
Real Time Image ◽  
Time Image
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