In this work, we introduce the concept of complex text style transfer ta...
Optical packet header recognition is an important signal processing task...
The low-rank adaptation (LoRA) method can largely reduce the amount of
t...
Second-order optimization algorithms exhibit excellent convergence prope...
To accelerate distributed training, many gradient compression methods ha...
Spoof localization, also called segment-level detection, is a crucial ta...
Event skeleton generation, aiming to induce an event schema skeleton gra...
Fracture is one of the main failure modes of engineering structures such...
Temporal heterogeneous information network (temporal HIN) embedding, aim...
It is widely agreed that reference-based super-resolution (RefSR) achiev...
Artificial intelligence (AI) has a history of nearly a century from its
...
Communication scheduling has been shown to be effective in accelerating
...
Photorealistic image generation from simulated label maps are necessitat...
Online social as an extension of traditional life plays an important rol...
Unlike tabular data, features in network data are interconnected within ...
Conditions are obtained for a Gaussian vector autoregressive time series...
Reference-based image super-resolution (RefSR) is a promising SR branch ...
We propose a new paradigm for zero-shot learners that is format agnostic...
As the categories of named entities rapidly increase in real-world
appli...
This paper reviews the Challenge on Super-Resolution of Compressed Image...
The second-order optimization methods, notably the D-KFAC (Distributed
K...
The academic literature of social sciences is the literature that record...
Stereo matching of high-resolution satellite images (HRSI) is still a
fu...
Deep learning has been widely applied for the channel state information ...
Automatic speaker verification is susceptible to various manipulations a...
The expansion of renewable energy could help realizing the goals of peak...
Federated Learning (FL) is an emerging distributed learning paradigm und...
Speaker embedding is an important front-end module to explore discrimina...
Stable and accurate electroencephalogram (EEG) signal acquisition is
fun...
Smart Internet of Vehicles (IoVs) combined with Artificial Intelligence ...
Deep learning (DL)-based channel state information (CSI) feedback improv...
The top 1 percent most highly cited articles are watched closely as the
...
We aim to improve the performance of multi-agent flocking behavior by
qu...
Semi-supervised video action recognition tends to enable deep neural net...
Automatic speaker verification (ASV) systems, which determine whether tw...
Multimodal learning has achieved great successes in many scenarios. Comp...
Retrieving occlusion relation among objects in a single image is challen...
We develop a Bayesian graphical modeling framework for functional data f...
Federated Deep Learning (FDL) is helping to realize distributed machine
...
In this paper, we provide a series of multi-tasking benchmarks for
simul...
The success of deep neural networks in real-world problems has prompted ...
Distributed training with synchronous stochastic gradient descent (SGD) ...
Contrastive learning applied to self-supervised representation learning ...
Temporal graph signals are multivariate time series with individual
comp...
Visual surface inspection is a challenging task owing to the highly dive...
Intelligent Transportation System (ITS) has become one of the essential
...
The development of the civil aviation industry has continuously increase...
All existing databases of spoofed speech contain attack data that is spo...
Pursuit-evasion games are ubiquitous in nature and in an artificial worl...
This study investigates the convergence of two bibliometric approaches t...