Abstract Sensor fusion is an important component of the perception system in autonomous driving, and radar point cloud information camera visual can improve capability vehicles. However, most existing studies ignore extraction local neighborhood only consider shallow between two modalities based on extracted global information, which cannot perform a deep cross-modal contextual interaction. Mea...

Existing object detection algorithms are affected by scenes with poor robustness, besides the existing public datasets not applicable to urban road traffic scenes. In order solve problems of low accuracy in detecting panoramic video images, high false rate, this article designed a real-time information method based on multi-scale feature fusion. For start, vehicle equipped hp-f515 driving recor...

This article considers the tracking of elliptical extended targets parameterized by center, orientation, and semiaxes. The focus this lies on fusion target estimates, e.g., from multiple sensors, handling ambiguities in parameterization unclear meaning mean square error. For purpose, we introduce a novel Bayesian framework for elliptic extent estimation based two new concepts: 1) A probability ...

Although methods based on the fully convolutional neural networks (FCNs) have shown strong advantages in field of salient object detection, existing still two challenging issues: insufficient multi-level feature fusion ability and boundary blur. To overcome these issues, we propose a novel detection method multi-feature cross network (denoted MFC-Net). Firstly, to issue ability, inspired by con...