Advances on cryo-electron imaging technologies have led to a rapidly
inc...
The goal of low-light image enhancement is to restore the color and deta...
With the fast-growing and evolving omics data, the demand for streamline...
Mental health significantly influences various aspects of our daily live...
Multi-modal fusion is increasingly being used for autonomous driving tas...
Current object detection models have achieved good results on many bench...
Medical artificial general intelligence (AGI) is an emerging field that ...
ChatGPT has drawn considerable attention from both the general public an...
A robust summarization system should be able to capture the gist of the
...
Deep learning based automatic medical image segmentation models often su...
Ensuring the reliability and availability of cloud services necessitates...
Automatic summarization plays an important role in the exponential docum...
Noise has always been nonnegligible trouble in object detection by creat...
Skin and subcutaneous diseases are among the major causes of the nonfata...
Efficient automatic segmentation of multi-level (i.e. main and branch)
p...
Heterogeneous data is endemic due to the use of diverse models and setti...
Revoking personal private data is one of the basic human rights, which h...
Drug combination therapy is a well-established strategy for disease trea...
Medical images are generally acquired with limited field-of-view (FOV), ...
Our work targets at searching feasible adversarial perturbation to attac...
Machine Learning-as-a-Service systems (MLaaS) have been largely develope...
In the field of medical image, deep convolutional neural networks(ConvNe...
Proper functioning of connected and automated vehicles (CAVs) is crucial...
Despite the success achieved in neural abstractive summarization based o...
Generalized Complete Intersection Calabi-Yau Manifold (gCICY) is a new
c...
Previous works for LiDAR-based 3D object detection mainly focus on the
s...
The success of deep neural networks greatly relies on the availability o...
One of the main challenges for feature representation in deep learning-b...
Skeleton extraction is a task focused on providing a simple representati...
The development of online economics arouses the demand of generating ima...
Image virtual try-on task has abundant applications and has become a hot...
Protein-RNA interactions are of vital importance to a variety of cellula...
The balance between high accuracy and high speed has always been a
chall...
In an autonomous driving system, it is essential to recognize vehicles,
...
Robust loss functions are essential for training deep neural networks wi...
Empirical natural language processing (NLP) systems in application domai...
For object detection in wide-area aerial imagery, post-processing is usu...
For state-of-the-art network function virtualization (NFV) systems, it
r...
In multi-tiered fog computing systems, to accelerate the processing of
c...
In fog-assisted IoT systems, it is a common practice to offload tasks fr...
In Fog-assisted IoT systems, it is a common practice to cache popular co...
For NFV systems, the key design space includes the function chaining for...
For wireless caching networks, the scheme design for content delivery is...
Mediation analysis has been used in many disciplines to explain the mech...
Since the first alert launched by the World Health Organization (5 Janua...
There is a recent surge of interest in designing deep architectures base...
Mediation analysis serves as a crucial tool to obtain causal inference b...
In this paper, we study a new representation-learning task, which we ter...
We consider a class of colored graphical Gaussian models obtained by pla...
Recent advances in deep learning have provided procedures for learning o...