Zobrazeno 1 - 10
of 18 424
pro vyhledávání: '"Multi-Modal"'
Autor:
Carrick, Ryan M., Brinkley, Taylor, Harvey, Cheyenne, Johnson, Ashtin, Penney, Taylor, Sauls, Tanner Kate, Kearney, Pamalyn J.
Publikováno v:
Quality in Ageing and Older Adults, 2024, Vol. 25, Issue 3, pp. 164-188.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/QAOA-11-2023-0080
Autor:
Zhangwei Gao, Zhe Chen, Erfei Cui, Yiming Ren, Weiyun Wang, Jinguo Zhu, Hao Tian, Shenglong Ye, Junjun He, Xizhou Zhu, Lewei Lu, Tong Lu, Yu Qiao, Jifeng Dai, Wenhai Wang
Publikováno v:
Visual Intelligence, Vol 2, Iss 1, Pp 1-17 (2024)
Abstract Multi-modal large language models (MLLMs) have demonstrated impressive performance in vision-language tasks across a wide range of domains. However, the large model scale and associated high computational cost pose significant challenges for
Externí odkaz:
https://doaj.org/article/fb58e6071c0d4a7998ba8b9a8f4f8a61
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-21 (2024)
Abstract Accurate identification of coal and gangue is a crucial guarantee for efficient and safe mining of top coal caving face. This article proposes a coal-gangue recognition method based on an improved beluga whale optimization algorithm (IBWO),
Externí odkaz:
https://doaj.org/article/c55b0998eeb5423689c84574feebc595
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-21 (2024)
Abstract Background The development of drug–target binding affinity (DTA) prediction tasks significantly drives the drug discovery process forward. Leveraging the rapid advancement of artificial intelligence, DTA prediction tasks have undergone a t
Externí odkaz:
https://doaj.org/article/a6082d8aefad4a1c84a09e1709b59d3b
Autor:
Matt Grote, Andrew Oakey, Aliaksei Pilko, Jakub Krol, Alex Blakesley, Tom Cherrett, James Scanlan, Bani Anvari, Antonio Martinez-Sykora
Publikováno v:
Transport Economics and Management, Vol 2, Iss , Pp 58-75 (2024)
Uncrewed Aerial Vehicles (UAVs; commonly known as drones) have been gaining interest as a potential transport mode for logistics (i.e., payload delivery), bringing suggested benefits such as reduced transit times and improved access in hard-to-reach
Externí odkaz:
https://doaj.org/article/8fa012519c00444882c91da2d539ede4
Publikováno v:
Language and Cognition, Vol 16, Pp 1987-2008 (2024)
Speakers of different languages follow a three-way split in how they express motion events in speech—with a greater emphasis on manner in satellite-framed languages (English), path in verb-framed languages (Turkish), and comparable expression of ma
Externí odkaz:
https://doaj.org/article/22dc0fc7412d41989b1ec303c845f0fb
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 1786-1795 (2024)
The rapid growth of spatially resolved transcriptomics technology provides new perspectives on spatial tissue architecture. Deep learning has been widely applied to derive useful representations for spatial transcriptome analysis. However, effectivel
Externí odkaz:
https://doaj.org/article/38c75f58ae0645099f30bf3164b7bed4
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Recently, impressive progress has been made in cross-domain image translation using image generation models pre-trained on massive amounts of data since these pre-trained generative models have strong generative capabilities.However, due to
Externí odkaz:
https://doaj.org/article/59d01d0c66ac46ae986c5de6969eaf2d
A lightweight approach to real-time speaker diarization: from audio toward audio-visual data streams
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2024, Iss 1, Pp 1-16 (2024)
Abstract This manuscript deals with the task of real-time speaker diarization (SD) for stream-wise data processing. Therefore, in contrast to most of the existing papers, it considers not only the accuracy but also the computational demands of indivi
Externí odkaz:
https://doaj.org/article/8b5037e2570e41bebdde2413729b9ef1
Publikováno v:
BioData Mining, Vol 17, Iss 1, Pp 1-30 (2024)
Abstract Background Timely identification of deteriorating patients is crucial to prevent the progression to cardiac arrest. However, current methods predicting emergency department cardiac arrest are primarily static, rule-based with limited precisi
Externí odkaz:
https://doaj.org/article/97640fd7f02c4404b84a6eac19422f24