A probabilistic neural network (PNN) is presented for predicting the magnitude of the largest
earthquake in a pre-defined future time period in a seismic region using eight …

Object detection, tracking and recognition in images are key problems in computer vision.
This book provides the reader with a balanced treatment between the theory and practice of …

A computational approach is presented for predicting the location and time of occurrence of
future moderate‐to‐large earthquakes in an approximate sense based on neural network …

Pattern recognition methods are used in the final stage of a traffic sign detection and
recognition system, where the main objective is to categorize a detected sign. Support vector …

Road sign recognition is a part of driver support systems. Its main aim is the increase of
traffic safety by calling the driver's attention to the presence of key traffic signs. Additionally, a …

There is a worldwide effort to apply 21st century intelligence to evolving our transportation
networks. The goals of smart transportation networks are quite noble and manifold, including …

Detection, recognition, and positioning of road signs are critical components of a roadway
asset management system. In this research, a stereo vision‐based system is developed to …

Template matching is a technique widely used for finding patterns in digital images. A good
template matching should be able to detect template instances that have undergone …

In this paper we propose efficient color segmentation method which is based on the Support
Vector Machine classifier operating in a one-class mode. The method has been developed …

Road signs are infrastructure assets crucial for transportation safety. Transportation
agencies need to inventory signs regularly, eg, annually or every 2 years, for asset …