Results 141 to 150 of about 9,194 (254)

A Novel Single‐Encounter‐Emphasise‐Attention Neural Network for Predictive Maintenance in Urban Infrastructure

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT The Riyadh Metro represents a significant project in Saudi Arabia, designed to transform urban transportation and reduce traffic congestion within the city. With six metro lines and 85 stations, the network is expected to serve millions of passengers daily, necessitating innovative digitally driven maintenance approaches to ensure reliable ...
Tawfeeq Shawly, Ahmed A. Alsheikhy
wiley   +1 more source

Gene knockout inference with variational graph autoencoder learning single-cell gene regulatory networks. [PDF]

open access: yesNucleic Acids Res, 2023
Yang Y   +7 more
europepmc   +1 more source

Efficient Masked Autoencoder for Birdsong Representation with Applications on Wild Bird Species Classification

open access: yesIntegrative Zoology, EarlyView.
Research on mosquito feeding preferences and the malaria parasites they transmit is essential for understanding the interactions between hosts, vectors, and parasites. In this study, vertebrate hosts were identified in 72 mosquitoes. Most blood meals (58.7%) came from birds, representing 25 species, while 40.0% came from mammals (13 species), and 1.3 ...
Qin Zhang   +8 more
wiley   +1 more source

Reusing Geospatial Data of Invasive Alien Insect Species From the Literature: Significance, Challenges, and Potential

open access: yesIntegrative Zoology, EarlyView.
We use bibliometric analysis to evaluate geospatial data reuse for invasive alien insect species (IAIS). Of 1032 relevant publications, 51.0% lacked downloadable raw data. Integrating cross‐regional, temporal, and multi‐species data could address single‐study limitations, but data scarcity remains a barrier.
Shuhao Tan   +5 more
wiley   +1 more source

VQ‐Style: Disentangling Style and Content in Motion with Residual Quantized Representations

open access: yesComputer Graphics Forum, EarlyView.
Abstract Human motion data is inherently rich and complex, containing both semantic content and subtle stylistic features that are challenging to model. We propose a novel method for effective disentanglement of the style and content in human motion data to facilitate style transfer.
Fatemeh Zargarbashi   +5 more
wiley   +1 more source

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