Title :
Higher-order decision surfaces in neural nets
Author_Institution :
Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
Several recent advances are described that use neural-network methods to produce the higher-order decision surface required for difficult pattern recognition discrimination problems. Work at Carnegie Mellon University is emphasized and includes new hyperspherical Ho-Kashyap neural nets and new piecewise quadratic neural nets. Also addressed are Fourier neural-net interconnections to handle multiple objects and achieve morphological, image processing, and enhancement functions
Keywords :
image recognition; neural nets; Carnegie Mellon University; Fourier neural-net interconnections; higher-order decision surface; hyperspherical Ho-Kashyap neural nets; image processing; image recognition; pattern recognition discrimination; piecewise quadratic neural nets; Feature extraction; Image analysis; Image processing; Image segmentation; Layout; Neural networks; Neurons; Nonlinear distortion; Pattern recognition; Surface morphology;
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
DOI :
10.1109/IJCNN.1992.227039
