Results 31 to 40 of about 1,027,441 (167)
Masked Structural Point Cloud Modeling to Learning 3D Representation
IEEE AccessPre-training for 3D object recognition typically requires a large-scale 3D dataset to learn effective 3D geometric representations. However, constructing such datasets is costly due to the extensive 3D data collection and human annotation required.
Ryosuke Yamada +4 more
doaj +1 more source
PCRDiff: A Perlin Noise-Based Cloud Removal Diffusion Model for Remote Sensing Images
Remote SensingRemote sensing imagery is a crucial component of remote sensing data. However, in its application to downstream tasks, cloud cover can hinder effective data utilization, making the removal of cloud occlusion from remote sensing images a persistent and ...
Danjun Liu +4 more
doaj +1 more source
IEEE Access, 2020 It is urgent to improve the physical reality of ocean scenes in marine simulator for the maritime industry. In this paper, we propose a unified anisotropic particle-based ocean wave simulation framework for marine simulator.
Haijiang Li +3 more
doaj +1 more source
Training Deep Learning Based Dynamic MR Image Reconstruction Using Synthetic Fractals
Magnetic Resonance in Medicine, EarlyView.ABSTRACT Purpose To investigate whether synthetically generated fractal data can be used to train deep learning (DL) models for dynamic MRI reconstruction, thereby avoiding the privacy, licensing, and availability limitations associated with cardiac MR training datasets.
Anirudh Raman +10 more
wiley +1 more source
Magnetic Resonance in Medicine, EarlyView.ABSTRACT Purpose Neural controlled differential equations (NCDEs) recently emerged as a robust deep learning approach for quantitative MRI parameter estimation. NCDEs offer flexibility to changes in acquisition protocols by modeling the signal evolution dynamics. However, NCDE implementations operate on a voxel‐by‐voxel basis and cannot exploit spatial
Daan Kuppens +5 more
wiley +1 more source
Quarterly Journal of the Royal Meteorological Society, EarlyView.Overconfident sea ice forecasts pose a challenge in subseasonal prediction. To test a potential way to address this issue and account for sea ice model uncertainty, this article investigates a stochastically perturbed parametrisations (SPP) scheme for sea ice in a prototype CY49R2 configuration of the coupled IFS‐NEMO4‐SI3 system. The results show that
Jonas Spaeth +7 more
wiley +1 more source
, 2001 International audienceWe propose a model of random fractal continuous-derivable procedural noise like Perlin textures, that is animated on a way similar to fluid motion, which a purely stochastic model cannot reproduce.
Perlin, Ken, Neyret, Fabrice
core
Remote SensingRemote sensing image dehazing aims to enhance the visibility of hazy images and improve the quality of remote sensing imagery, which is essential for various applications such as object detection and classification.
Yitong Zheng +4 more
doaj +1 more source
3-D Simulation of Double-Bar Plush Fabrics with Jacquard Patterns
AUTEX Research Journal, 2018 A realistic computerized simulation of double-bar plush fabrics can result in a time-saving development process with high quality. Based on basic analysis of jacquard principles, a fast 3-D simulation method of warp-knitted plush fabrics is proposed by ...
Zhang Aijun +4 more
doaj +1 more source
Perlin Noise Generation of Physiologically Realistic Patterns of Fibrosis [PDF]
, 2019 Abstract Fibrosis, the pathological excess of fibroblast activity, is a significant health issue that hinders the function of many organs in the body, in some cases fatally. However, the severity of fibrosis-derived conditions depends on both the positioning of fibrotic affliction, and the microscopic patterning of ...
Jakes, David +7 more
openaire +1 more source