Hand geometry identification without feature extraction by general regression neural network
Expert Systems with Applications: An International Journal
A general regression neural network
IEEE Transactions on Neural Networks
Neuro semantic thresholding using OCR software for high precision OCR applications
Image and Vision Computing
Dimension reduction by a novel unified scheme using divergence analysis and genetic search
Digital Signal Processing
Journal of Medical Systems
Expert Systems with Applications: An International Journal
User-oriented ontology-based clustering of stored memories
Expert Systems with Applications: An International Journal
Computer Methods and Programs in Biomedicine
Data mining applied to the cognitive rehabilitation of patients with acquired brain injury
Expert Systems with Applications: An International Journal
Generalized classifier neural network
Neural Networks
An automatic computer-aided diagnosis system for liver tumours on computed tomography images
Computers and Electrical Engineering
Hi-index | 12.06 |
The remote detection of undersea mines in shallow waters using active sonar is a crucial subject required to maintain the security of important harbors and cost line areas. The discrimination sonar returns from mines and returns from rocks on the sea floor by human experts is usually difficult and very heavy workload. Neural network classifiers have been widely used in classification of complex sonar signals due to its adaptive and parallel processing ability. In this paper, due to the advantages on fast learning and convergence to the optimal regression surface as the number of samples becomes very large, general regression neural network (GRNN) has been used to solve the problem of classification underwater targets. Principal component analysis (PCA) has been established as a feature extraction method to improve classification performance. Receiver operating characteristic (ROC) analysis has been applied to the neural classifier to evaluate the sensitivity and specificity of diagnostic procedures.