Retraction Notice: Sora-Based Parallel Vision for Smart Sensing of Intelligent Vehicles: From Foundation Models to Foundation Intelligence

There are a large number of functional sensors installed on the modern intelligent vehicles. Many Artificial Intelligence based foundation models have been proposed for smart sensing to recognize the known object classes in the new but similar scenarios. However, it is still challenging for the foundation models of smart sensing to detect all the object classes in both seen and unseen scenarios. This letter aims at pushing the boundary of smart sensing research for intelligent vehicles. We first summarize the current widely-used foundation models and the foundation intelligence needed for smart sensing of intelligent vehicles. We then explain Sora-based Parallel Vision to boost the foundation models of smart sensing from basic intelligence (1.0) to enhanced intelligence (2.0) and final generalized intelligence (3.0). Several representative case studies are discussed to show the potential usages of Sora-based Parallel Vision, followed by its future research direction.

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Publication Details

Journal
IEEE Transactions on Intelligent Vehicles
Published
2024-11-20
DOI
https://doi.org/10.1109/tiv.2024.3502550
Citations
2
Primary Topic
Infrared Target Detection Methodologies
Type
article
Field-Weighted Citation Impact
2.60
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article

Retraction Notice: Sora-Based Parallel Vision for Smart Sensing of Intelligent Vehicles: From Foundation Models to Foundation Intelligence

Hongkai Yu, Chao Gou, Yonglin Tian, Xinyu Liu et al.
2 citations
IEEE Transactions on Intelligent Vehicles
Infrared Target Detection Methodologies
2.60
article

Retraction Notice: Sora-Based Parallel Vision for Smart Sensing of Intelligent Vehicles: From Foundation Models to Foundation Intelligence

Hongkai Yu, Chao Gou, Yonglin Tian, Xinyu Liu, Yutong Wang, Fei‐Yue Wang
article en
2 citations

Abstract

There are a large number of functional sensors installed on the modern intelligent vehicles. Many Artificial Intelligence based foundation models have been proposed for smart sensing to recognize the known object classes in the new but similar scenarios. However, it is still challenging for the foundation models of smart sensing to detect all the object classes in both seen and unseen scenarios. This letter aims at pushing the boundary of smart sensing research for intelligent vehicles. We first summarize the current widely-used foundation models and the foundation intelligence needed for smart sensing of intelligent vehicles. We then explain Sora-based Parallel Vision to boost the foundation models of smart sensing from basic intelligence (1.0) to enhanced intelligence (2.0) and final generalized intelligence (3.0). Several representative case studies are discussed to show the potential usages of Sora-based Parallel Vision, followed by its future research direction.

IEEE Transactions on Intelligent Vehicles
Cleveland State University (US), Sun Yat-sen University (CN), Shenzhen University (CN), Chinese Academy of Sciences (CN), Institute of Automation (CN)
Openalex Percentile: Top 8%
Infrared Target Detection Methodologies
2.60
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