Zobrazeno 1 - 10
of 5 225
pro vyhledávání: '"YANG, Le"'
Autor:
Yang, Le
This article proposes a novel algorithm for solving mismatch problem in compressed sensing. Its core is to transform mismatch problem into matched by constructing a new measurement matrix to match measurement value under unknown measurement matrix. T
Externí odkaz:
http://arxiv.org/abs/2410.22354
Differentiable architecture search (DARTS) has emerged as a promising technique for effective neural architecture search, and it mainly contains two steps to find the high-performance architecture: First, the DARTS supernet that consists of mixed ope
Externí odkaz:
http://arxiv.org/abs/2409.14433
Generic event boundary detection (GEBD), inspired by human visual cognitive behaviors of consistently segmenting videos into meaningful temporal chunks, finds utility in various applications such as video editing and. In this paper, we demonstrate th
Externí odkaz:
http://arxiv.org/abs/2407.12622
Generic event boundary detection (GEBD) aims at pinpointing event boundaries naturally perceived by humans, playing a crucial role in understanding long-form videos. Given the diverse nature of generic boundaries, spanning different video appearances
Externí odkaz:
http://arxiv.org/abs/2407.04274
Recent proposed neural network-based Temporal Action Detection (TAD) models are inherently limited to extracting the discriminative representations and modeling action instances with various lengths from complex scenes by shared-weights detection hea
Externí odkaz:
http://arxiv.org/abs/2407.03197
This paper presents a cross-layer video delivery scheme, StreamOptix, and proposes a joint optimization algorithm for video delivery that leverages the characteristics of the physical (PHY), medium access control (MAC), and application (APP) layers.
Externí odkaz:
http://arxiv.org/abs/2406.04632
Autor:
Cheng, Hao, Xiao, Erjia, Yang, Jiayan, Cao, Jiahang, Zhang, Qiang, Yang, Le, Zhang, Jize, Xu, Kaidi, Gu, Jindong, Xu, Renjing
Recently, Multimodal Large Language Models (MLLMs) achieve remarkable performance in numerous zero-shot tasks due to their outstanding cross-modal interaction and comprehension abilities. However, MLLMs are found to still be vulnerable to human-imper
Externí odkaz:
http://arxiv.org/abs/2405.20090
Adaptive bitrate (ABR) using conventional codecs cannot further modify the bitrate once a decision has been made, exhibiting limited adaptation capability. This may result in either overly conservative or overly aggressive bitrate selection, which co
Externí odkaz:
http://arxiv.org/abs/2406.02557
Autor:
Xu, Xingyan, Cai, Yingying, Wu, Siying, Guo, Jianhui, Yang, Le, Lan, Jieli, Sun, Yi, Wang, Bingbing, Wu, Jieyu, Wang, Tinggui, Huang, Shuna, Lin, Yawen, Hu, Yuduan, Chen, Mingjun, Gao, Xuecai, Xie, Xiaoxu
Publikováno v:
Journal of Medical Internet Research, Vol 23, Iss 1, p e21825 (2021)
BackgroundInternet hospitals in China are being rapidly developed as an innovative approach to providing health services. The ongoing COVID-19 pandemic has triggered the development of internet hospitals that promote outpatient service delivery to th
Externí odkaz:
https://doaj.org/article/ffa6fd6e94214636847a32fdc7a28184
Spoken language understanding (SLU), one of the key enabling technologies for human-computer interaction in IoT devices, provides an easy-to-use user interface. Human speech can contain a lot of user-sensitive information, such as gender, identity, a
Externí odkaz:
http://arxiv.org/abs/2403.15510