Deep learning has developed as an effective machine learning method that takes in
numerous layers of features or representation of the data and provides state-of-the-art …

In vision-enabled autonomous systems such as robots and autonomous cars, video object
detection plays a crucial role, and both its speed and accuracy are important factors to …

In the process of coal mining, the coal quality is greatly reduced due to the mixing of gangue,
and the stacking and burning of coal and gangue can cause serious environmental …

In order to solve the problem that, in complex and wide traffic scenes, the accuracy and
speed of multi-object detection can hardly be balanced by the existing object detection …

With the end of conventional CMOS scaling, efficient resiliency solutions are needed to
address the increased likelihood of hardware errors. Silent data corruptions (SDCs) are …

Deep-learning convolutional neural networks (CNNs) have proven to be successful in
various cognitive applications with a multilayer structure. The high computational energy …

Object detection is a very important part of computer vision, and the most common method of
object detection is the Faster region convolutional neural network (RCNN), which uses CNN …

Multi-object tracking (MOT) plays a crucial role in various platforms. Occlusion and insertion
among targets, complex backgrounds and higher real-time requirements increase the …

Real-time object detection is crucial in autonomous driving. To avoid catastrophic accidents,
an autonomous car should detect objects with multiple cameras and make decisions within …

The processing requirement of autonomous vehicles (AVs) for high-accuracy perception in
complex scenarios can exceed the resources offered by the in-vehicle computer, degrading …