16 research outputs found
3D Object Recognition Using Multiple Views And Neural Networks.
This paper proposes a method for recognition and classification of 3D objects. The method is based on 2D moments and neural networks. The 2D moments are calculated based on 2D intensity images taken from multiple cameras that have been arranged using multiple views technique. 2D moments are commonly used for 2D pattern recognition
New Features of Cervical Cells for Cervical Cancer Diagnostic System Using Neural Network.
Currently, Pap test is the most popular and effective test for cervical cancer. However, Pap test does not always produce good diagnostic performance. This problem has encouraged several studies to develop diagnosis system based on neural networks to increase the diagnostic performance
Performance Comparison Between HMLP, MLP And Recurrent Networks With Applications To Carbon Monoxide Concentrations Forecasting.
This paper compares the performance of Hybrid Multilayered Perceptron (HMLP) network, Multilayered Perceptron (MLP) network and Recurrent network. These networks are used to model and forecast carbon monoxide (CO) concentration
Segmentation Of Stretched Pap Smear Cytology Images Using Clustering Algorithm.
Papanicolaou test or better known as Pap test is the most popular and effective screening test for cervical cancer. At time, however, the detection of abnormal or cancerous cervical cells can be missed due to technical and human errors
International Journal of the Computer, the Internet and Management Model Validity Tests for RBF Network
Model validation is an important step in system identification process. However, theoretical derivation of model validity tests for neural network such as RBF network is very complicated. The current study, investigate the capability of some of the model validity tests that are widely been used namely one step ahead prediction, model predicted output, means square error and correlation tests. This paper also explores the appropriateness of these validity tests to provide some inside information about network model deficiencies