Short-term traffic flow forecasting at isolated points is a fundamental yet challenging task in
many intelligent transportation systems. We present a novel long short-term memory (LSTM) …

Data-free knowledge distillation is a challenging model lightweight task for scenarios in which
the original dataset is not available. Previous methods require a lot of extra computational …

Aerial image object detection remains rather challenging, due to the small object gathering
and confusion of inter-class similarities and intra-class diversity. Confronting such challenges…

We investigate traffic scene detection from surveillance cameras and UAVs. This task is
rather challenging, mainly due to the spatial nonuniform gathering, large-scale variance, and …

We investigate vehicle density detection from traffic surveillance. This task is rather challenging,
mainly due to the low-resolution of data and large-scale variance of vehicles. The main …

Data-Free Knowledge Distillation (DFKD) is a novel task that aims to train high-performance
student models using only the pre-trained teacher network without original training data. …

In this paper, we explore the potential of using the multivoxel proton magnetic resonance
spectroscopy ( 1 H‐MRS) to diagnose neuropsychiatric systemic lupus erythematosus (NPSLE) …

The neuropsychiatric systemic lupus erythematosus (NPSLE) has higher disability and
mortality rates, which is one of the main causes of death in systemic lupus erythematosus (SLE) …

From source to target, point cloud registration solves for a rigid body transformation that aligns
the two point clouds. IterativeClosest Point (ICP) and other traditional algorithms require a …

Interpolation consistency is a consistency regularization technique in semi-supervised
learning (SSL), which encourages the model’s prediction of the interpolated samples to be …