Title :
A multilayer perceptron feature extractor for reading sequenced DNA autoradiograms
Author :
Murdock, Michael C. ; Cotter, Neil E. ; Gesteland, Raymond
Author_Institution :
Adv. Artificial Intelligence Lab., Motorola Gov. Electron. Group, Scottsdale, AZ, USA
fDate :
30 Sep-1 Oct 1991
Abstract :
The authors report on the application of the three-layer, backward error propagation neural network to the problem of reading sequenced DNA autoradiograms. The network is used for band identification by extracting two features: band intensity level and band intensity gradient. A training set of 16000 12×12 gray scale patterns is generated. Trained with these patterns, the network successfully learned to identify the degree of presence and absence of these two low level features
Keywords :
DNA; backpropagation; biological techniques and instruments; feature extraction; image processing; learning (artificial intelligence); neural nets; radioisotope scanning and imaging; backward error propagation neural network; band intensity gradient; gray scale patterns; multilayer perceptron feature extractor; sequenced DNA autoradiograms; three-layer network; Biomedical imaging; Cities and towns; DNA; Data mining; Feature extraction; Humans; Multilayer perceptrons; Neural networks; Sequences; Visual system;
Conference_Titel :
Neural Networks for Signal Processing [1991]., Proceedings of the 1991 IEEE Workshop
Conference_Location :
Princeton, NJ
Print_ISBN :
0-7803-0118-8
DOI :
10.1109/NNSP.1991.239485
