scholarly journals Detecting Fraudulent Bank Checks

2017 ◽  
pp. 245-266 ◽  
Author(s):  
Saheb Chhabra ◽  
Garima Gupta ◽  
Monika Gupta ◽  
Gaurav Gupta
Keyword(s):  
Bank Checks

Data fusion approach to verifying handwritten signatures on bank checks

1999 ◽  
Author(s):  
D. J. Scott ◽  
Otman A. Basir ◽  
Khaled S. Hassanein ◽  
John S. Zelek
Keyword(s):  
Data Fusion ◽  
Bank Checks ◽  
Fusion Approach

Thresholding the Courtesy Amount of Brazilian Bank Checks Based on Tsallis Entropy

2009 ◽  
Vol 7 (6) ◽  
pp. 726-731 ◽  
Author(s):  
Renata Neves ◽  
Carlos Mello ◽  
Maira Silva ◽  
Byron Bezerra
Keyword(s):  
Tsallis Entropy ◽  
Bank Checks

Recognizing Hand-Printed Letters and Digits Using Backpropagation Learning

1991 ◽  
Vol 3 (2) ◽  
pp. 258-267 ◽  
Author(s):  
Gale L. Martin ◽  
James A. Pittman
Keyword(s):  
Character Recognition ◽  
High Performance ◽  
Network Capacity ◽  
Training Sample ◽  
Error Rates ◽  
Training Set ◽  
Set Size ◽  
Bank Checks ◽  
Recognition Systems ◽  
High Recognition Accuracy

We report on results of training backpropagation nets with samples of hand-printed digits scanned off of bank checks and hand-printed letters interactively entered into a computer through a stylus digitizer. Generalization results are reported as a function of training set size and network capacity. Given a large training set, and a net with sufficient capacity to achieve high performance on the training set, nets typically achieved error rates of 4-5% at a 0% reject rate and 1-2% at a 10% reject rate. The topology and capacity of the system, as measured by the number of connections in the net, have surprisingly little effect on generalization. For those developing hand-printed character recognition systems, these results suggest that a large and representative training sample may be the single, most important factor in achieving high recognition accuracy. Benefits of reducing the number of net connections, other than improving generalization, are discussed.

scholarly journals HANDWRITTEN BANK CHECK RECOGNITION OF COURTESY AMOUNTS

2004 ◽  
Vol 04 (02) ◽  
pp. 203-222 ◽  
Author(s):  
RAFAEL PALACIOS ◽  
AMAR GUPTA ◽  
PATRICK S. WANG
Keyword(s):  
Neural Network ◽  
Large Scale ◽  
Rapid Evolution ◽  
Hybrid Architecture ◽  
Neural Network Classifier ◽  
Bank Checks

In spite of rapid evolution of electronic techniques, a number of large-scale applications continue to rely on the use of paper as the dominant medium. This is especially true for processing of bank checks. This paper examines the issue of reading the numerical amount field. In the case of checks, the segmentation of unconstrained strings into individual digits is a challenging task because of connected and overlapping digits, broken digits, and digits that are physically connected to pieces of strokes from neighboring digits. The proposed architecture involves four stages: segmentation of the string into individual digits, normalization, recognition of each character using a neural network classifier, and syntactic verification. Overall, this paper highlights the importance of employing a hybrid architecture that incorporates multiple approaches to provide high recognition rates.

A filtering algorithm for highly noisy images of Brazilian ATM bank checks

2009 ◽  
Author(s):  
Carlos A.B. Mello ◽  
Byron L.D. Bezerra ◽  
Afonso G.A. Ferreira ◽  
Juliano C.B. Rabelo
Keyword(s):  
Filtering Algorithm ◽  
Noisy Images ◽  
Bank Checks

Agents and Payment Systems in E-Commerce

2001 ◽  
pp. 317-330 ◽  
Author(s):  
Feng Hua ◽  
Sheng-Uei Guan
Keyword(s):  
Mobile Agent ◽  
World Wide ◽  
Research Area ◽  
Payment Systems ◽  
Internet Commerce ◽  
Agent Based ◽  
Bank Checks ◽  
Financial Infrastructure ◽  
New Research ◽  
Cryptographic Techniques

Since the 1990s, the World Wide Web has brought about innumerable changes to the ways enterprises do business. Electronic commerce is emerging as one of the most important applications on the Internet. The use of agents in e-commerce is a new research area. Agents can provide effective, fast, and cheap ways to make deals and execute transactions in cyberspace. Abstract representations of value have been developed from metal, paper notes, and bank checks to savings cards, credit cards, and now electronic forms. This chapter presents a brief survey of existing different types of payment systems and focuses on mobile agent-based computing trends in e-commerce. By combining software agent technology with cryptographic techniques, an agent-based e-payment scheme built for the SAFER e-commerce architecture is proposed, which is aimed to provide a flexible and secure financial infrastructure for Internet commerce.

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