Object Detection in Autonomous Driving Scenarios Based on an Improved Faster-RCNN
-
Published:2021-12-08
Issue:24
Volume:11
Page:11630
-
ISSN:2076-3417
-
Container-title:Applied Sciences
-
language:en
-
Short-container-title:Applied Sciences
Author:
Zhou Yan,Wen Sijie,Wang Dongli,Mu Jinzhen,Richard Irampaye
Abstract
Object detection is one of the key algorithms in automatic driving systems. Aiming at addressing the problem of false detection and the missed detection of both small and occluded objects in automatic driving scenarios, an improved Faster-RCNN object detection algorithm is proposed. First, deformable convolution and a spatial attention mechanism are used to improve the ResNet-50 backbone network to enhance the feature extraction of small objects; then, an improved feature pyramid structure is introduced to reduce the loss of features in the fusion process. Three cascade detectors are introduced to solve the problem of IOU (Intersection-Over-Union) threshold mismatch, and side-aware boundary localization is applied for frame regression. Finally, Soft-NMS (Soft Non-maximum Suppression) is used to remove bounding boxes to obtain the best results. The experimental results show that the improved Faster-RCNN can better detect small objects and occluded objects, and its accuracy is 7.7% and 4.1% respectively higher than that of the baseline in the eight categories selected from the COCO2017 and BDD100k data sets.
Funder
National Natural Science Foundation of China
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
16 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Evaluación comparativa del rendimiento de modelos de detección de residuos en entornos urbanos;REVISTA AMBIENTAL AGUA, AIRE Y SUELO;2024-05-10
2. Research on multi-object detection technology for road scenes based on SDG-YOLOv5;PeerJ Computer Science;2024-04-30
3. Road Traffic Accident Prediction using Deep Learning;2024 International Conference on Cognitive Robotics and Intelligent Systems (ICC - ROBINS);2024-04-17
4. Sow Behavior Object Detection Network Using Swin Transformer;2023 13th International Conference on Information Science and Technology (ICIST);2023-12-08
5. Driving Perception in Challenging Road Scenarios: An Empirical Study;2023 20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA);2023-12-04