The large-scale visual-language pre-trained model, Contrastive Language-...
This paper presents a Multiple Kernel Learning (abbreviated as MKL) fram...
Large language models (LLMs) have demonstrated powerful capabilities in ...
Food image-to-recipe aims to learn an embedded space linking the rich
se...
We formulate the Multiple Kernel Learning (abbreviated as MKL) problem f...
We consider the problem to estimate the generalized cepstral coefficient...
Current video generation models usually convert signals indicating appea...
We introduce VISOR, a new dataset of pixel annotations and a benchmark s...
Generating large-scale samples of stationary random fields is of great
i...
Federated learning (FL) enables multiple clients to collaboratively trai...
Cross-modal recipe retrieval has attracted research attention in recent
...
Recent studies have found that removing the norm-bounded projection and
...
Labeled datasets are essential for supervised machine learning. Various ...
News recommendation is critical for personalized news distribution. Fede...
This paper presents a fast algorithm to solve a spectral estimation prob...
Recent work shows that deep neural networks are vulnerable to adversaria...
In this paper, we propose the pyramid fusion dark channel prior (PF-DCP)...
As the successor of H.265/HEVC, the new versatile video coding standard
...
In object detection, offset-guided and point-guided regression dominate
...
Group cohesiveness is a compelling and often studied composition in grou...