… that YOLOv4 is currently the best choice for road object detection with exceptionally good
detection accuracy and speed compared to the previous one-stage and two-stage detectors. …

… object detection and localization in on-road environment using deep neural network. We
compared the detection accuracy among object … Single shot multibox detector on KITTI dataset. …

… the best choice for road object detection with exceptionally good detection accuracy, fast …
-stage and two-stage detectors. Recently, a new object detection algorithm based on YOLOv3 […

… The road object detection model in this paper is based on the publicly available Darknet-53
and Tensorflow of YOLOv3. In the experiment of this paper, we use NVIDIA GTX 1080ti and …

… objects on the road to improve driving safety. This section reviews mainly the object detection
… On the one hand, radar-based object detection uses millimeter-wave (mm-wave) to de…

… the road surface information extraction and road object detection. The road surface
information includes different kinds of road pavement, road markings, and driving lines. While …

… is well proven in urban object detection and extraction, since … -of-the-art road object detection
and extraction methods using … systems are suitable for supporting road asset inventory, ITS-…

… Road object detection is an essential and imperative step for driving intelligent vehicles.
Generally, road objects… puts a high demand on the detection algorithm. Therefore, this paper …

… With all of this in mind, we think widespread research on 3D object detection will be slow to
emerge … resources can collect a custom training set and apply our object detection approach. …

… This makes it a perfect fit for our detection system as we aim to detect road objects. Kitti
dataset consists of 7481 training images with seven labeled classes: cars, van, tram, trucks, …