DocumentCode
2725836
Title
Gestures and neural networks in human-computer interaction
Author
Beale, Russell ; Edwards, Alistair D N
Author_Institution
Dept. of Comput. Sci., York Univ., UK
fYear
1991
fDate
8-14 Jul 1991
Abstract
Summary form only given. Neural networks are recognized as being able to learn to solve classification problems, and their generalization properties make them suitable for interpreting imprecise input values. These features of neural networks were utilized by applying networks to the problem of recognizing gestural input. The signs made by a user are interpreted and classified by the network, allowing a natural method of communication between the user and the system
Keywords
computerised pattern recognition; neural nets; user interfaces; classification problems; generalization; gestural input; human-computer interaction; imprecise input values; neural networks; signs; Artificial neural networks; Backpropagation; Computer science; Constraint optimization; Design optimization; Intelligent networks; Mechanical engineering; Neural networks; Neurons; Pattern classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location
Seattle, WA
Print_ISBN
0-7803-0164-1
Type
conf
DOI
10.1109/IJCNN.1991.155467
Filename
155467
Link To Document