In the cooperative cellular network, relay-like base stations are connec...
Previous researchers conducting Just-In-Time (JIT) defect prediction tas...
The degradation process of lithium-ion batteries is intricately linked t...
High-definition (HD) map provides abundant and precise static environmen...
Event camera-based pattern recognition is a newly arising research topic...
Publishing streaming data in a privacy-preserving manner has been a key
...
Machine learning and neural networks have become increasingly popular
so...
This paper investigates the problem of regret minimization for multi-arm...
Sampled point and voxel methods are usually employed to downsample the d...
Learning based feature matching methods have been commonly studied in re...
Data with missing values is ubiquitous in many applications. Recent year...
To alleviate the local receptive issue of GCN, Transformers have been
ex...
The power and flexibility of Optimal Transport (OT) have pervaded a wide...
Autonomous driving requires a comprehensive understanding of the surroun...
Online lane graph construction is a promising but challenging task in
au...
Existing cross-domain keypoint detection methods always require accessin...
Motion prediction is highly relevant to the perception of dynamic object...
Combining the Color and Event cameras (also called Dynamic Vision Sensor...
Exploring sample relationships within each mini-batch has shown great
po...
The main streams of human activity recognition (HAR) algorithms are deve...
Given a dissimilarity matrix, the metric nearness problem is to find the...
Quantized constant envelope (QCE) precoding, a new transmission scheme t...
Magnetic resonance images play an essential role in clinical diagnosis b...
Graph Attention Networks (GATs) have been intensively studied and widely...
Few-shot classification which aims to recognize unseen classes using ver...
We introduce a Dimension-Reduced Second-Order Method (DRSOM) for convex ...
In this report, we introduce our solution to the Occupancy and Flow
Pred...
The purpose of this study is to explore students' backtracking patterns ...
Training deep learning (DL) models has become a norm. With the emergence...
Graph Convolutional Networks (GCNs) have been widely demonstrated their
...
Recently, transformer-based methods have achieved promising progresses i...
We introduce in this paper a new statistical perspective, exploiting the...
Graph neural networks (GNNs) have achieved great success in many graph
l...
In this paper, we consider the problem of answering count queries for ge...
The varying coefficient model has received wide attention from researche...
Salient object detection (SOD) on RGB-D images is an active problem in
c...
We propose a kernel-based partial permutation test for checking the equa...
In this paper, we consider the one-bit precoding problem for the multius...
This paper considers the one-bit precoding problem for the multiuser dow...
A networked time series (NETS) is a family of time series on a given gra...
Deep generative models have made great progress in synthesizing images w...
In this paper, we introduce a proximal-proximal majorization-minimizatio...
The multiple-input multiple-output (MIMO) detection problem, a fundament...
Scale variance is one of the crucial challenges in multi-scale object
de...
Video anomaly detection is commonly used in many applications such as
se...
Influence maximization (IM) aims at maximizing the spread of influence b...
Segmentation-based tracking has been actively studied in computer vision...
Many popular blockchain platforms are supporting smart contracts for bui...
EOSIO is one typical public blockchain platform. It is scalable in terms...
Recently, Batch DropBlock network (BDB) has demonstrated its effectivene...