Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Yu, Xiangxu"'
In this study, we present a quantitative and comprehensive analysis of social gaze in people with autism spectrum disorder (ASD). Diverging from traditional first-person camera perspectives based on eye-tracking technologies, this study utilizes a th
Externí odkaz:
http://arxiv.org/abs/2409.00664
Autor:
Hu, Chuanbo, Thrasher, Jacob, Li, Wenqi, Ruan, Mindi, Yu, Xiangxu, Paul, Lynn K, Wang, Shuo, Li, Xin
Diagnosing autism spectrum disorder (ASD) by identifying abnormal speech patterns from examiner-patient dialogues presents significant challenges due to the subtle and diverse manifestations of speech-related symptoms in affected individuals. This st
Externí odkaz:
http://arxiv.org/abs/2405.05126
Diagnosing language disorders associated with autism is a complex and nuanced challenge, often hindered by the subjective nature and variability of traditional assessment methods. Traditional diagnostic methods not only require intensive human effort
Externí odkaz:
http://arxiv.org/abs/2405.01799
How can we teach a computer to recognize 10,000 different actions? Deep learning has evolved from supervised and unsupervised to self-supervised approaches. In this paper, we present a new contrastive learning-based framework for decision tree-based
Externí odkaz:
http://arxiv.org/abs/2304.10073
In recent years, with the vigorous development of the video game industry, the proportion of gaming videos on major video websites like YouTube has dramatically increased. However, relatively little research has been done on the automatic quality pre
Externí odkaz:
http://arxiv.org/abs/2204.00128
The rising popularity of online User-Generated-Content (UGC) in the form of streamed and shared videos, has hastened the development of perceptual Video Quality Assessment (VQA) models, which can be used to help optimize their delivery. Gaming videos
Externí odkaz:
http://arxiv.org/abs/2203.12824
Blind or no-reference video quality assessment of user-generated content (UGC) has become a trending, challenging, heretofore unsolved problem. Accurate and efficient video quality predictors suitable for this content are thus in great demand to achi
Externí odkaz:
http://arxiv.org/abs/2101.10955
Autor:
Madhusudana, Pavan C., Yu, Xiangxu, Birkbeck, Neil, Wang, Yilin, Adsumilli, Balu, Bovik, Alan C.
Publikováno v:
IEEE Access. 9 (2021) 108069 - 108082
High frame rate (HFR) videos are becoming increasingly common with the tremendous popularity of live, high-action streaming content such as sports. Although HFR contents are generally of very high quality, high bandwidth requirements make them challe
Externí odkaz:
http://arxiv.org/abs/2007.11634
Autor:
Yu, Xiangxu, Birkbeck, Neil, Wang, Yilin, Bampis, Christos G., Adsumilli, Balu, Bovik, Alan C.
Over the past decade, the online video industry has greatly expanded the volume of visual data that is streamed and shared over the Internet. Moreover, because of the increasing ease of video capture, many millions of consumers create and upload larg
Externí odkaz:
http://arxiv.org/abs/2004.02943
Virtual Reality (VR) and its applications have attracted significant and increasing attention. However, the requirements of much larger file sizes, different storage formats, and immersive viewing conditions pose significant challenges to the goals o
Externí odkaz:
http://arxiv.org/abs/1910.03074