To better detect pedestrians of various scales, deep multi-scale methods usually detect pedestrians of different scales by different in-network layers. However, the semantic levels of features from different layers are usually inconsistent. In this paper, we propose a multi-branch and high-level semantic network by gradually splitting a base network into multiple different branches. As a result...

The integrated network provides the diverse application to the user. WiMAX is the most promising high speed broadband access with full QoS and WLAN provides high data rate at low cost, for limited coverage area. Integrated WiMAX-WLAN network can be capable of providing ubiquitous connectivity and high data rate to the end user. This paper focuses on the comparative performance analyzing of inte...

Although many deep-learning-based methods have achieved considerable detection performance for pedestrians with high visibility, their overall performances are still far from satisfactory, especially when heavily occluded instances included. In this research, we developed a novel pedestrian detector using deformable attention-guided network (DAGN). Considering that may be deformed occlusions or...

Crowdsensing, people tracking and urban space utilization are critical tasks for understanding human behavior in smart cities. Human sensing applications provide valuable feedback to the urban developers and architects to optimize public facilities and re-invent spaces. In this chapter, a Renewable Wireless Sensor Network (RWSN) architecture for human sensing is presented to study the spatial a...

Recently, advanced driver assistance systems (ADAS) have attracted wide attention in pedestrian detection for using the multi-spectrum generated by multi-sensors. However, it is quite challenging image-based sensors to perform their tasks due instabilities such as light changes, object shading, or weather conditions. Considering all above, based on different spectral information of RGB and ther...