Abstract Segmentation of complex and diverse scenes in the field machine vision has advantages low cost good robustness. However, real open intelligent driving scene, segmented object will be affected by change proportion illumination. The feature extraction interference algorithm causes some problems such as local information loss background fusion process execution. In this paper, deep neural...

Abstract Aiming at the problem of strong impact, short response period and wide resonance frequency bandwidth transient vibration signals, a feature extraction method based on adaptive tunable Q-factor wavelet transform (TQWT) was proposed. Firstly, characteristic band signal selected according to time–frequency distribution. Based band, sub-band average energy weighted Shannon entropy used opt...

Abstract Epilepsy is a nervous system disease, which caused by abnormal discharge of brain neurons. The clinical manifestations are generalized seizures, clonus, loss consciousness, and shock. An electroencephalogram (EEG) can accurately capture the changes in EEG activities. Therefore, signals used to detect seizures. In this paper, an epilepsy detection model based on time-gated feature netwo...

Pedestrians are important traffic participants and prediction of pedestrian crossing intention can help reduce pedestrian–vehicle collisions. For the problem predicting an individual pedestrian’s action where there is potential, a method that considers multi-feature fusion proposed in this study, which integrates information affecting pedestrians’ actions, such as environment. This study based ...