We present an image segmentation algorithm that is based on spatially adaptive color and texture features. The proposed algorithm is based on a previously proposed algorithm but introduces a number of new elements. We use a new set of texture features based on a steerable filter decomposition. The steerable filters combined with a new spatial texture segmentation scheme provide a finer and more...

This paper proposes a switching adaptive control for trajectory tracking of unmanned aircraft systems. The switching adaptive control method is designed to overcome the wind disturbance and achieve a proper tracking performance for control systems. In the suggested system, the wind disturbance is regarded as a finite set of uncertainties; a controller is designed for each uncertainty, and a per...

Scene segmentation is widely used in autonomous driving for environmental perception. Semantic scene (3S) has gained considerable attention owing to its rich semantic information. It assigns labels the pixels an image, thereby enabling automatic image labeling. Current approaches are based mainly on convolutional neural networks (CNN), however, they rely numerous labels. Therefore, use of a sma...

The Robust and reliable traffic information detection from images acquired by traffic surveillance system is an important problem with numerous applications including adaptive traffic signal control system and traffic analysis system. This paper describes an application of computer vision techniques to traffic surveillance. The objective in this paper is to improve the efficiency of traffic flo...

Aiming at solving the existing sharp problems in impact signal detection by using stochastic resonance (SR) in the fault diagnosis of rotating machinery, such as the measurement index selection of SR and the detection of impact signal with different impact amplitudes, the present study proposes an adaptive SR method for impact signal detection based on sliding window by analyzing the SR charact...

It is often needed to label electroencephalogram (EEG) signals by segments of similar characteristics that are particularly meaningful to clinicians and for assessment by neurophysiologists. Within each segment, the signals are considered statistically stationary, usually with similar characteristics such as amplitude and/or frequency. In order to detect the segments boundaries of a signal, we ...