H
Hu Cao
Researcher at Technische Universität München
Publications - 11
Citations - 317
Hu Cao is an academic researcher from Technische Universität München. The author has contributed to research in topics: Neuromorphic engineering & Convolutional neural network. The author has an hindex of 5, co-authored 11 publications receiving 120 citations. Previous affiliations of Hu Cao include Hunan University.
Papers
More filters
Journal ArticleDOI
Event-Based Neuromorphic Vision for Autonomous Driving: A Paradigm Shift for Bio-Inspired Visual Sensing and Perception
TL;DR: It is expected that this article will serve as a starting point for new researchers and engineers in the autonomous driving field and provide a bird's-eye view to both neuromorphic vision and autonomous driving research communities.
Journal ArticleDOI
Neuromorphic Vision Based Multivehicle Detection and Tracking for Intelligent Transportation System
Guang Chen,Guang Chen,Hu Cao,Muhammad Aafaque,Jieneng Chen,Canbo Ye,Florian Röhrbein,Jörg Conradt,Kai Chen,Zhenshan Bing,Xingbo Liu,Gereon Hinz,Walter Stechele,Alois Knoll +13 more
TL;DR: The first neuromorphic vision based multivehicle detection and tracking system in ITS is proposed and the performance of the system is evaluated with a dataset recorded by a neuromorph vision sensor mounted on a highway bridge.
Posted Content
Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation.
TL;DR: Wang et al. as mentioned in this paper proposed a pure transformer-based U-shaped Encoder-Decoder architecture with skip-connections for local-global semantic feature learning for medical image segmentation.
Journal ArticleDOI
Multi-Cue Event Information Fusion for Pedestrian Detection With Neuromorphic Vision Sensors.
Guang Chen,Hu Cao,Canbo Ye,Zhenyan Zhang,Xingbo Liu,Xuhui Mo,Zhongnan Qu,Jörg Conradt,Florian Röhrbein,Alois Knoll +9 more
TL;DR: This work proposes to develop pedestrian detectors that unlock the potential of the event data by leveraging multi-cue information and different fusion strategies, and introduces three different event-stream encoding methods based on Frequency, Surface of Active Event (SAE) and Leaky Integrate-and-Fire (LIF).
Journal ArticleDOI
Parking Slot Detection on Around-View Images Using DCNN.
TL;DR: A parking slot detection method that uses directional entrance line regression and classification based on a deep convolutional neural network (DCNN) to make it robust and simple and achieves a real-time detection speed of 13 ms per frame on Titan Xp.