This paper introduces autonomous driving image perception technology, including deep learning models (such as CNN and RNN) and their applications, analyzing the limitations of traditional algorithms. It elaborates on the shortcomings of Faster R-CNN and YOLO series models, proposes various improvement techniques such as data fusion, attention mechanisms, and model compression, and introduces relevant datasets, evaluation metrics, and testing frameworks to demonstrate the advantages of the improved models.
Wen LH, Jo KH, 2022, Deep Learning-Based Perception Systems for Autonomous Driving: A Comprehensive Survey. Neurocomputing, 489: 255–270.
Huang Y, Chen Y, 2020, Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies. arXiv preprint, arXiv: 2006.06091.
Grigorescu S, Trasnea B, Cocias T, et al., 2020, A Survey of Deep Learning Techniques for Autonomous Driving. Journal of field robotics, 37(3): 362–386.
Jebamikyous HH, Kashef R, 2022, Autonomous Vehicles Perception (AVP) Using Deep Learning: Modeling, Assessment, and Challenges. IEEE Access, 10: 10523–10535.
Fayyad J, Jaradat MA, Gruyer D, et al., 2020, Deep Learning Sensor Fusion for Autonomous Vehicle Perception and Localization: A Review. Sensors, 20(15): 4220.
Alaba SY, Ball JE, 2023, Deep Learning-Based Image 3-D Object Detection for Autonomous Driving. IEEE Sensors Journal, 23(4): 3378–3394.
Li G, Yang Y, Qu X, et al., 2021, A Deep Learning Based Image Enhancement Approach for Autonomous Driving at Night. Knowledge-Based Systems, 213: 106617.
Zhang J, Cao J, Chang J, et al., 2023, Research on the Application of Computer Vision Based on Deep Learning in Autonomous Driving Technology, International Conference on Wireless Communications, Networking and Applications, Springer Nature Singapore, Singapore, 82–91.
Lee DH, Chen KL, Liou KH, et al., 2021, Deep Learning and Control Algorithms of Direct Perception for Autonomous Driving. Applied Intelligence, 51(1): 237–247.
Tahir NM, Bature UI, Baba MA, et al., 2020, Image Recognition Based Autonomous Driving: A Deep Learning Approach. Int. J. Eng. Manuf, 10(6): 11–19.