Stochastic Gradient Descent (SGD), a widely used optimization algorithm ...
Recently, the fast development of Large Language Models (LLMs) such as
C...
Multiple object tracking (MOT) has been successfully investigated in com...
Automated code generation can be a powerful technique for software
devel...
We present a one-shot method to infer and render a photorealistic 3D
rep...
Recommendation systems have witnessed significant advancements and have ...
Automatic and periodic recompiling of building databases with up-to-date...
Gabor wavelet is an essential tool for image analysis and computer visio...
The generalized Hamming weight of linear codes is a natural generalizati...
The core problem of text-based person retrieval is how to bridge the
het...
Given a natural language description, text-based person retrieval aims t...
In the context of distributed deep learning, the issue of stale weights ...
Nonunion is one of the challenges faced by orthopedics clinics for the
t...
Registering urban point clouds is a quite challenging task due to the
la...
Knowledge graph embedding methods are important for knowledge graph
comp...
With the multi-dimensional exploration towards oceans, enormous sensing ...
Single-stage detectors suffer from extreme foreground-background class
i...
In this paper, we propose a novel design, called MixNN, for protecting d...
Automated machine learning systems for non-experts could be critical for...
Task-oriented dialogue systems have become overwhelmingly popular in rec...
The echo state network (ESN) is a special type of recurrent neural netwo...
Accurate position sensing is important for state estimation and control ...
Static graph neural networks have been widely used in modeling and
repre...
Graph neural networks can be effectively applied to find solutions for m...
We develop the concept of Trusted and Confidential Program Analysis (TCP...
Learned image compression techniques have achieved considerable developm...
Adversarial attacks attempt to disrupt the training, retraining and util...
In this paper, we propose a learned video codec with a residual predicti...
State-of-the-art asynchronous Byzantine fault-tolerant (BFT) protocols, ...
Truss robots are highly redundant parallel robotic systems and can be ap...
In an autonomous driving system, it is essential to recognize vehicles,
...
Motion planning in high-dimensional space is a challenging task. In orde...
Self-assembly of modular robotic systems enables the construction of com...
Decentralized finance, i.e., DeFi, has become the most popular type of
a...
Restoring images from low-light data is a challenging problem. Most exis...
Low-light image enhancement, such as recovering color and texture detail...
Code search is a core software engineering task. Effective code search t...
Attention based neural TTS is elegant speech synthesis pipeline and has ...
Convolutional neural network (CNN)-based filters have achieved great suc...
Convolutional Neural Network (CNN)-based filters have achieved significa...
Reverse-engineering bar charts extracts textual and numeric information ...
Deep learning (DL) techniques have gained significant popularity among
s...
To accelerate software development, developers frequently search and reu...
Background: Elderly patients with MODS have high risk of death and poor
...
In this paper, a dual learning-based method in intra coding is introduce...
The clinical treatment of degenerative and developmental lumbar spinal
s...
Deep Learning has established itself to be a common occurrence in the
bu...
The goal of salient region detection is to identify the regions of an im...
In this paper we present DELTA, a deep learning based language technolog...
Depth sensing is crucial for 3D reconstruction and scene understanding.
...