Occlusion Handling and Multi-scale Pedestrian Detection Based on Deep Learning: A Review

Pedestrian detection is an important branch of computer vision, and it has important applications in the fields of autonomous driving, artificial intelligence and video surveillance.With the rapid development of deep learning and the proposal of large-scale datasets, pedestrian detection has reached a new stage and achieves better performance...

Shape feature aided target detection method for micro-drone surveillance radar

This paper presents a shape feature aided target detection method for micro-drone surveillance radar in order to mitigate the false alarms caused by the ground clutter. The method consists of a segmentation threshold selection method based on target measurements and a shape-feature extraction method based on Hu moments. Then the performance...

Spectrum-Based Hand Gesture Recognition Using Millimeter-Wave Radar Parameter Measurements

Radar sensors offer several advantages over optical sensors in the gesture recognition for remote control of electronic devices. In this paper, we investigate the feasibility of human gesture recognition using the spectra of radar measurement parameters. With the combination of radar theory and classification methods, we found that the...

Automatic Defect Detection of Fasteners on the Catenary Support Device Using Deep Convolutional Neural Network

The excitation and vibration triggered by the long-term operation of railway vehicles inevitably result in defective states of catenary support devices. With the massive construction of high-speed electrified railways, automatic defect detection of diverse and plentiful fasteners on the catenary support device is of great significance for...

Planetary gears feature extraction and fault diagnosis method based on VMD and CNN

Given local weak feature information, a novel feature extraction and fault diagnosis method for planetary gears based on variational mode decomposition (VMD), singular value decomposition (SVD), and convolutional neural network (CNN) is proposed. VMD was used to decompose the original vibration signal to mode components. The mode matrix was...