Results 221 to 230 of about 8,133 (257)

Dynamic Feature Fusion for Sparse Radar Detection: Motion-Centric BEV Learning with Adaptive Task Balancing. [PDF]

Sensors (Basel)
Sang Y, Cui J, Sun Y, Zhang F, Li Y, Shi G.   +5 more
europepmc   +1 more source

BMPCQA: Bioinspired Metaverse Point Cloud Quality Assessment Based on Large Multimodal Models

Advanced Intelligent Systems, EarlyView.
This study presents a bioinspired metaverse point cloud quality assessment metric, which simulates the human visual evaluation process to perform the point cloud quality assessment task. It first extracts rendering projection video features, normal image features, and point cloud patch features, which are then fed into a large multimodal model to ...
Huiyu Duan, Kang Fu, Sijing Wu, Yunhao Li, Zicheng Zhang, Qiang Hu, Xiongkuo Min, Guangtao Zhai   +7 more
wiley   +1 more source

Urban emissions and expansion intensify extreme precipitation and flood susceptibility in Texas. [PDF]

NPJ Nat Hazards
Moraglia G, Aboelnour M, Crippa P.
europepmc   +1 more source

Discrepancies in Arctic-boreal lake area trends driven by sensitivity to dry conditions. [PDF]

Sci Rep
Webb EE, Cooley SW, Levenson E, Maze J.
europepmc   +1 more source

Evidence for the gravity-driven and magnetically regularized gas flows feeding the massive protostellar cluster in Cepheus A. [PDF]

Sci Adv
Sandhyarani P, Eswaraiah C, Li D, Vázquez-Semadeni E, Gómez GC, Thieme TJ, Samal MR, Wang JW, Lai SP, Chen WP, Ojha DK.   +10 more
europepmc   +1 more source

Challenges in global climate models to represent cloud response to aerosols: insights from volcanic eruptions. [PDF]

Nat Commun
Wang Y, Neubauer D, Chen Y, Jordan G, Malavelle F, Yuan T, Partridge D, Field P, Wang H, Wang M, Michou M, Nabat P, Laakso A, Myhre G, Lohmann U.   +14 more
europepmc   +1 more source

BN-NeRF: A fast 3D reconstruction and phenotyping framework for banana plants using handheld devices. [PDF]

Plant Phenomics
Xu X, Chen S, Liu Y, Duan J, Jin M, Fu H, Yang Z.   +6 more
europepmc   +1 more source

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Efficient data IO for a Parallel Global Cloud Resolving Model

Environmental Modelling and Software, 2011
Execution of a Global Cloud Resolving Model (GCRM) at target resolutions of 2-4 km will generate, at a minimum, 10s of Gigabytes of data per variable per snapshot. Writing this data to disk, without creating a serious bottleneck in the execution of the GCRM code, while also supporting efficient post-execution data analysis is a significant challenge ...
Bruce J Palmer, David A Randall
exaly   +2 more sources