Space-air-ground integrated networks (SAGINs), which have emerged as an
...
While recent innovations on shape technologies allow for the creation of...
We study the capabilities of speech processing systems trained simply to...
Computing is a critical driving force in the development of human
civili...
We tackle the task of NeRF inversion for style-based neural radiance fie...
Extreme multi-label text classification (XMTC) refers to the problem of
...
Predicting the trajectory of stochastic dynamical systems (SDSs) is an
i...
This work aims to provide an effective deep learning framework to predic...
One of the most significant challenges of EEG-based emotion recognition ...
Text embeddings are useful features in many applications such as semanti...
We show how to derive state-of-the-art unsupervised neural machine
trans...
In many applications of computer graphics, art and design, it is desirab...
With the rapid development of deep learning, many deep learning based
ap...
Optoelectronic tweezer-driven microrobots (OETdMs) are a versatile
micro...
We train a single, goal-conditioned policy that can solve many robotic
m...
To unlock video chat for hundreds of millions of people hindered by poor...
In this paper, we study efficient differentially private alternating
dir...
In this paper, we present a workflow for the simulation of drone operati...
Differentiable Neural Architecture Search (DNAS) has demonstrated great
...
Uterine cancer, also known as endometrial cancer, can seriously affect t...
The application to search ranking is one of the biggest machine learning...
Objective: Ultrahigh-resolution optical coherence microscopy (OCM) has
r...
Image feature point matching is a key step in Structure from Motion(SFM)...
Multiobjective optimization evolutionary algorithms have been successful...
The word "valley" is a popular term used in intuitively describing fitne...
Convolutional neural networks are powerful tools for image segmentation ...
Bronchoscopy inspection as a follow-up procedure from the radiological
i...
In this paper, we propose an Attentional Generative Adversarial Network
...
Generative adversarial training can be generally understood as minimizin...
Although Generative Adversarial Networks (GANs) have shown remarkable su...
Inspired by classic generative adversarial networks (GAN), we propose a ...
Synthesizing high-quality images from text descriptions is a challenging...
Solving constrained optimization problems by multi-objective evolutionar...
Structure information is ubiquitous in natural scene images and it plays...
In object recognition, Fisher vector (FV) representation is one of the
s...