A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Curve and surface constructions using rational B-splines
Computer-Aided Design
PHIGS+ functional description revision
ACM SIGGRAPH Computer Graphics
Choosing nodes in parametric curve interpolation
Computer-Aided Design
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
IEEE Computer Graphics and Applications
SURFACES FOR COMPUTER-AIDED DESIGN OF SPACE FORMS
SURFACES FOR COMPUTER-AIDED DESIGN OF SPACE FORMS
Color Characterization and Balancing by a Nonlinear Line Attractor Network for Image Enhancement
Neural Processing Letters
Binary Image Thinning Using Autowaves Generated by PCNN
Neural Processing Letters
Nonlinear blind source separation by spline neural networks
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 05
Rational B-Splines for Curve and Surface Representation
IEEE Computer Graphics and Applications
IEEE Transactions on Signal Processing
Low bit rate subband DCT image compression
IEEE Transactions on Consumer Electronics
Artifact reduction in low bit rate DCT-based image compression
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Concealment of damaged block transform coded images using projections onto convex sets
IEEE Transactions on Image Processing
Image coding making use of B-spline surfaces
IEEE Transactions on Circuits and Systems for Video Technology
Recovery of corrupted image data based on the NURBS interpolation
IEEE Transactions on Circuits and Systems for Video Technology
Multilayer feedforward networks with adaptive spline activation function
IEEE Transactions on Neural Networks
Weight assignment for adaptive image restoration by neural networks
IEEE Transactions on Neural Networks
Nonlinear system modeling via knot-optimizing B-spline networks
IEEE Transactions on Neural Networks
Application of adaptive constructive neural networks to image compression
IEEE Transactions on Neural Networks
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A novel bi-variate non-uniform rational B-splines (NURBS) surface neural network consisting of four hidden layers is proposed in this paper. The blending functions are selected as the activation functions for the neurons in one of the hidden layers, instead of the commonly used sigmoid functions. With mathematical derivations, it is easy to find that the mathematical expression of the output of the proposed neural network is exactly the same as the NURBS surface. Since a set of 2-D gray scale image data can be considered as a 3-D surface, therefore the proposed NURBS surface neural network can be applied to deal with image processing problems. Two experiments, concerning image compression and corrupted image restoration, are conducted to demonstrate the feasibility of the proposed approach.