Deep learning, a branch of machine learning, is a frontier for artificial intelligence, aiming to
be closer to its primary goal—artificial intelligence. This paper mainly adopts the summary …

This work explores and compares the plethora of metrics for the performance evaluation of
object-detection algorithms. Average precision (AP), for instance, is a popular metric for …

Recent outstanding results of supervised object detection in competitions and challenges
are often associated with specific metrics and datasets. The evaluation of such methods …

Driving intelligence tests are critical to the development and deployment of autonomous
vehicles. The prevailing approach tests autonomous vehicles in life-like simulations of the …

In this paper, we present a comprehensive review of the imbalance problems in object
detection. To analyze the problems in a systematic manner, we introduce a problem-based …

Object detection, one of the most fundamental and challenging problems in computer vision,
seeks to locate object instances from a large number of predefined categories in natural …

Perception system design is a vital step in the development of an autonomous vehicle (AV).
With the vast selection of available off-the-shelf schemes and seemingly endless options of …

Timely monitoring of pavement cracks is essential for successful maintenance of road
infrastructure. Accurate information concerning crack location and severity enables proactive …

Autonomous vehicle (AV) technology can provide a safe and convenient transportation
solution for the public, but the complex and various environments in the real world make it …

Object detection can be regarded as one of the most fundamental and challenging visual
recognition task in computer vision and it has received great attention over the past few …