Improving Autonomous Vehicle Visual Perception by Fusing Human Gaze and Machine Vision-Reference-Cited by-同舟云学术

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Improving Autonomous Vehicle Visual Perception by Fusing Human Gaze and Machine Vision

Published:2023-11 Issue:11 Volume:24 Page:12716-12725
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Zhao Yiyue¹^ORCID,Lei Cailin²^ORCID,Shen Yu²^ORCID,Du Yuchuan²^ORCID,Chen Qijun³^ORCID

Affiliation:

1. School of Vehicle and Mobility, Tsinghua University, Haidian, China

2. Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai, China

3. Frontiers Science Center for Intelligent Autonomous Systems, Tongji University, Shanghai, China

Funder

National Key Research and Development Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/10304348/10194417.pdf?arnumber=10194417

Reference42 articles.

1. Road detection using segmentation by weighted aggregation based on visual information and a posteriori probability of road regions

2. You Only Look Once: Unified, Real-Time Object Detection

3. Generalizing the Hough transform to detect arbitrary shapes

4. Reducing the Dimensionality of Data with Neural Networks

5. Microsoft COCO: Common objects in context;lin;Vision Computer,2014

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1. A review of object tracking methods: From general field to autonomous vehicles;Neurocomputing;2024-06

2. 4D mmWave Radar for Autonomous Driving Perception: A Comprehensive Survey;IEEE Transactions on Intelligent Vehicles;2024-04

3. Enhanced Scene Understanding and Situation Awareness for Autonomous Vehicles Based on Semantic Segmentation;IEEE Transactions on Systems, Man, and Cybernetics: Systems;2024

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