Recent years have witnessed the great success of vision transformer (ViT...
Weakly supervised object localization (WSOL) is one of the most popular ...
Recently, the efficient deployment and acceleration of powerful vision
t...
Entanglement serves as the resource to empower quantum computing. Recent...
This paper studies multiparty learning, aiming to learn a model using th...
Cross domain pulmonary nodule detection suffers from performance degrada...
Lung cancer is the leading cause of cancer death worldwide. The best sol...
Federated learning aims to collaboratively train models without accessin...
New architecture GPUs like A100 are now equipped with multi-instance GPU...
Depression is a leading cause of death worldwide, and the diagnosis of
d...
Incorrect placement of methods within classes is a typical code smell ca...
Few-shot visual recognition refers to recognize novel visual concepts fr...
Many fundamental properties of a quantum system are captured by its
Hami...
Convolutional neural networks (CNNs) have been demonstrated to be highly...
Few-shot part segmentation aims to separate different parts of an object...
Recently, deploying deep neural network (DNN) models via collaborative
i...
Recently, the compression and deployment of powerful deep neural network...
The goal of unpaired image captioning (UIC) is to describe images withou...
Generating informative scene graphs from images requires integrating and...
Dependency parsing aims to extract syntactic dependency structure or sem...
Scene Graph Generation (SGG) aims to build a structured representation o...
AI engineering has emerged as a crucial discipline to democratize deep n...
A key problem in the field of quantum computing is understanding whether...
DNN-based video analytics have empowered many new applications (e.g.,
au...
Combining video streaming and online retailing (V2R)
has been a growing ...
Given the massive market of advertising and the sharply increasing onlin...
The digital retina in smart cities is to select what the City Eye tells ...
The features used in many image analysis-based applications are frequent...
Distance metric learning (DML) plays a crucial role in diverse machine
l...
The goal of transfer learning is to improve the performance of target
le...
In computer vision, image datasets used for classification are naturally...
There is growing interest in multi-label image classification due to its...
Distance metric learning (DML) is a critical factor for image analysis a...
Feature selection is beneficial for improving the performance of general...
Distance metric learning (DML) aims to find an appropriate way to reveal...
Recruitment of appropriate people for certain positions is critical for ...
The generalized partial credit model (GPCM) is a popular polytomous IRT ...
Canonical correlation analysis (CCA) has proven an effective tool for
tw...