Zobrazeno 1 - 10
of 548
pro vyhledávání: '"Liang Xuefeng"'
Previous Facial Beauty Prediction (FBP) methods generally model FB feature of an image as a point on the latent space, and learn a mapping from the point to a precise score. Although existing regression methods perform well on a single dataset, they
Externí odkaz:
http://arxiv.org/abs/2409.00603
Large Language Models (LLMs) have greatly contributed to the development of adaptive intelligent agents and are positioned as an important way to achieve Artificial General Intelligence (AGI). However, LLMs are prone to produce factually incorrect in
Externí odkaz:
http://arxiv.org/abs/2408.07611
Publikováno v:
Open Medicine, Vol 15, Iss 1, Pp 702-708 (2020)
Forkhead box K2 (FOXK2) was first identified as an NFAT-like interleukin-binding factor. FOXK2 has been reported to act as either oncogene or tumor suppressor. However, functional and regulating mechanisms of FOXK2 in epithelial–mesenchymal transit
Externí odkaz:
https://doaj.org/article/a6fc7de204d14ebbb0572c8a40f99522
Autor:
Jiang Xiaofeng, Ni Ziwei, Feng Qiao, Guo Hongtao, Fu Dongge, Wang Junmian, Zhou Hongtao, Liang Xuefeng, Ruan Cailian
Publikováno v:
BIO Web of Conferences, Vol 61, p 01005 (2023)
This study aimed to explore the effect of treadmill exercise on anxiety in rats. Thirty SPF male rats aged 2 months with a body mass of (225±25) g were randomly divided into control group (CG, n=10), chronic sleep deprivation group (CSD, n=10) and s
Externí odkaz:
https://doaj.org/article/d550deced00b4383956007cd3043cb74
Multimodal learning has exhibited a significant advantage in affective analysis tasks owing to the comprehensive information of various modalities, particularly the complementary information. Thus, many emerging studies focus on disentangling the mod
Externí odkaz:
http://arxiv.org/abs/2401.16119
Subjective time-series regression (STR) tasks have gained increasing attention recently. However, most existing methods overlook the label distribution bias in STR data, which results in biased models. Emerging studies on imbalanced regression tasks,
Externí odkaz:
http://arxiv.org/abs/2307.07682
In speech emotion recognition tasks, models learn emotional representations from datasets. We find the data distribution in the IEMOCAP dataset is very imbalanced, which may harm models to learn a better representation. To address this issue, we prop
Externí odkaz:
http://arxiv.org/abs/2302.08650
Publikováno v:
In Information Fusion February 2025 114
Publikováno v:
In Pattern Recognition January 2025 157
Samples in large-scale datasets may be mislabeled due to various reasons, and Deep Neural Networks can easily over-fit to the noisy label data. To tackle this problem, the key point is to alleviate the harm of these noisy labels. Many existing method
Externí odkaz:
http://arxiv.org/abs/2202.09579