79 citations · 208 across the 21 of their papers we have counts for
21 papers
Resistive memory-based zero-shot liquid state machine for multimodal event data learning
Ning Lin, Shaocong Wang, Yi Li +19
The human brain is a complex spiking neural network (SNN), capable of learning multimodal signals in a zero-shot manner by generalizing existing knowledge. Remarkably, it maintains…
RNGDet++: Road Network Graph Detection by Transformer with Instance Segmentation and Multi-scale Features Enhancement
Zhenhua Xu, Yuxuan Liu, Yuxiang Sun +2
The road network graph is a critical component for downstream tasks in autonomous driving, such as global route planning and navigation. In the past years, road network graphs are…
Monocular Camera Mapping with Pose-Guided Optimization: Enhancing Marking-Level HD Map Accuracy
Hongji Liu, Linwei Zheng, Xiaoyang Yan +4
Marking-level high-definition maps (HD maps) are of great significance for autonomous vehicles (AVs), especially in large-scale, appearance-changing scenarios where AVs rely on mar…
CenterLineDet: CenterLine Graph Detection for Road Lanes with Vehicle-mounted Sensors by Transformer for HD Map Generation
Zhenhua Xu, Yuxuan Liu, Yuxiang Sun +2
With the fast development of autonomous driving technologies, there is an increasing demand for high-definition (HD) maps, which provide reliable and robust prior information about…
Real-time Neural Dense Elevation Mapping for Urban Terrain with Uncertainty Estimations
Bowen Yang, Qingwen Zhang, Ruoyu Geng +2
Having good knowledge of terrain information is essential for improving the performance of various downstream tasks on complex terrains, especially for the locomotion and navigatio…
All-optical nanoscale thermometry based on silicon-vacancy centers in detonation nanodiamonds
Masanori Fujiwara, Gaku Uchida, Izuru Ohki +5
Silicon-vacancy (SiV) centers in diamond are a promising candidate for all-optical nanoscale high-sensitivity thermometry because they have sufficient sensitivity to reach the subk…
Open-world Semantic Segmentation for LIDAR Point Clouds
Jun Cen, Peng Yun, Shiwei Zhang +5
Current methods for LIDAR semantic segmentation are not robust enough for real-world applications, e.g., autonomous driving, since it is closed-set and static. The closed-set assum…
Real-Time Trajectory Planning for Autonomous Driving with Gaussian Process and Incremental Refinement
Cheng Jie, Chen Yingbing, Zhang Qingwen +2
Real-time kinodynamic trajectory planning in dynamic environments is critical yet challenging for autonomous driving. In this letter, we propose an efficient trajectory planning sy…
Channel Self-Supervision for Online Knowledge Distillation
Shixiao Fan, Xuan Cheng, Xiaomin Wang +5
Recently, researchers have shown an increased interest in the online knowledge distillation. Adopting an one-stage and end-to-end training fashion, online knowledge distillation us…
RNGDet: Road Network Graph Detection by Transformer in Aerial Images
Zhenhua Xu, Yuxuan Liu, Lu Gan +4
Road network graphs provide critical information for autonomous-vehicle applications, such as drivable areas that can be used for motion planning algorithms. To find road network g…
Why-So-Deep: Towards Boosting Previously Trained Models for Visual Place Recognition
M. Usman Maqbool Bhutta, Yuxiang Sun, Darwin Lau +1
Deep learning-based image retrieval techniques for the loop closure detection demonstrate satisfactory performance. However, it is still challenging to achieve high-level performan…
Echo state graph neural networks with analogue random resistor arrays
Shaocong Wang, Yi Li, Dingchen Wang +13
Recent years have witnessed an unprecedented surge of interest, from social networks to drug discovery, in learning representations of graph-structured data. However, graph neural…
Open-set 3D Object Detection
Jun Cen, Peng Yun, Junhao Cai +2
3D object detection has been wildly studied in recent years, especially for robot perception systems. However, existing 3D object detection is under a closed-set condition, meaning…
Temporally Resolution Decrement: Utilizing the Shape Consistency for Higher Computational Efficiency
Tianshu Xie, Xuan Cheng, Minghui Liu +3
Image resolution that has close relations with accuracy and computational cost plays a pivotal role in network training. In this paper, we observe that the reduced image retains re…
A New Continuous Optimization Method for Mixed Integer Space Travelling Salesman Problem
Liqiang Hou, Shufan Wu, Zhongcheng Mu +1
The travelling salesman problem (TSP) of space trajectory design is complicated by its complex structure design space. The graph based tree search and stochastic seeding combinator…
White Paper Assistance: A Step Forward Beyond the Shortcut Learning
Xuan Cheng, Tianshu Xie, Xiaomin Wang +3
The promising performances of CNNs often overshadow the need to examine whether they are doing in the way we are actually interested. We show through experiments that even over-par…
FocusedDropout for Convolutional Neural Network
Tianshu Xie, Minghui Liu, Jiali Deng +3
In convolutional neural network (CNN), dropout cannot work well because dropped information is not entirely obscured in convolutional layers where features are correlated spatially…
Road Crack Detection Using Deep Convolutional Neural Network and Adaptive Thresholding
Rui Fan, Mohammud Junaid Bocus, Yilong Zhu +5
Crack is one of the most common road distresses which may pose road safety hazards. Generally, crack detection is performed by either certified inspectors or structural engineers.…
A Task Allocation Schema Based on Response Time Optimization in Cloud Computing
Kai Li, Yong Wang, Meilin Liu
Cloud computing is a newly emerging distributed computing which is evolved from Grid computing. Task scheduling is the core research of cloud computing which studies how to allocat…
A Non-Cooperative Game Model for Reliability-Based Task Scheduling in Cloud Computing
Kai Li, Yong Wang, Meilin Liu
Cloud computing is a newly emerging distributed system which is evolved from Grid computing. Task scheduling is the core research of cloud computing which studies how to allocate t…
Experimental observation of ferrielectricity in multiferroic DyMn2O5: revisiting the electric polarization
Z. Y. Zhao, M. F. Liu, X. Li +4
The electric polarization and its magnetic origins in multiferroic RMn2O5, where R is rare-earth ion, are still issues under debate. In this work, the temperature-dependent electri…