Monitoring of protected areas to curb illegal activities like poaching and animal trafficking is
a monumental task. To augment existing manual patrolling efforts, unmanned aerial …

In surveillance applications, the detection of tiny, low-resolution objects remains a
challenging task. Most deep learning object detection methods rely on appearance features …

It has been recognized that deeper and wider neural networks are continuously advancing
the state-of-the-art performance of various computer vision and machine learning tasks …

Edge computing extends computing power down to the network edge near the sensors and
provides promising solutions to address high bandwidth requirements and latency-sensitive …

We introduce a new large-scale data set of video URLs with densely-sampled object
bounding box annotations called YouTube-BoundingBoxes (YT-BB). The data set consists …

Deep learning models have significantly improved object detection, which is essential for
visual sensing. However, their increasing complexity results in higher latency and resource …

Intelligent unmanned aerial vehicles (UAVs) are drawing more and more attention from
industry to academia. UAV navigation plays an important role in the cooperative scenario …

Video object detection enhances the performance of the still-image based object detection
by exploiting temporal context information from neighboring frames. Most of the state-of-the …

Efficient and adaptive computer vision systems have been proposed to make computer
vision tasks, such as image classification and object detection, optimized for embedded or …

Object detection in streaming images is a major step in different detection-based
applications, such as object tracking, action recognition, robot navigation, and visual …