Considering the labeled samples may be difficult to obtain because they require human
annotators, special devices, or expensive and slow experiments. Semi-supervised learning …

Pedestrian detection is an important but challenging problem in computer vision, especially
in human-centric tasks. Over the past decade, significant improvement has been witnessed …

Multispectral pedestrian detection is an important functionality in various computer vision
applications such as robot sensing, security surveillance, and autonomous driving. In this …

In this paper, we present a pedestrian detection method by leveraging multispectral images
which consist of color and thermal image information. Our method is based on the …

Multimodal information (eg, visible and thermal) can generate robust pedestrian detections
to facilitate around-the-clock computer vision applications, such as autonomous driving and …

Barrier coverage is a fundamental application in wireless sensor networks, which are widely
used for smart cities. In applications, the sensors form a barrier for the intruders and protect …

Recently, an increasing number of algorithms have been proposed for rain streak removal.
However, most existing methods ignore the discrepancy in removing rain streaks from …

Pedestrian detection is one of the most challenging research areas in computer vision, as it
involves classifying the image and localizing the pedestrian. Its applications, especially in …

To fulfill the tasks of human-robot interaction (HRI), how to detect the specific human (SH)
becomes paramount. In this paper, the deep learning approach by the integration of Single …

In face recognition, searching a person's face in the whole picture is generally too time‐
consuming to ensure high‐detection accuracy. Objects similar to the human face or multi …