Results 61 to 70 of about 1,027,441 (167)

Environmental Controls on the Seasonal and Spatial Variability of Submesoscale Thermal Air–Sea Coupling Over the Gulf Stream

open access: yesGeophysical Research Letters, Volume 53, Issue 5, 16 March 2026.
Abstract Using an ocean‐atmosphere coupled simulation, we investigate the seasonal variability of the low‐level wind response to submesoscale (O(1–10 km)) sea surface temperature (SST) anomalies over the Gulf Stream, focusing on the respective roles of the downwind momentum mixing (DMM) and pressure adjustment (PA) mechanisms.
Lionel Renault   +2 more
wiley   +1 more source

Perlin noise functions for generation of textures

open access: yes, 2012
This work deals with Perlin noise function in theoretical and practical way. Procedural textures can be generated by Perlin noise function. Perlin´s algorithm has many advantages, for example natural appearance, smaller demands on memory capacity and ...
Jakubíková, Radka
core  

Implementasi Perlin noise pada simulasi kabut heterogen Gunung Kelud [PDF]

open access: yes, 2020
INDONESIA: Perkembangan teknologi game dan simulasi 3D masih berlangsung. Banyak bermunculan game dan simulasi dengan teknologi tampilan mirip aslinya atau realistis.
Cahyani, Berlian Gita
core  

Improving semantic segmentation accuracy in thin cloud interference scenarios by mixing simulated cloud-covered samples

open access: yesInternational Journal of Applied Earth Observations and Geoinformation
Thin cloud interference presents a significant challenge for the semantic segmentation of optical satellite imagery, which directly degrades the model accuracy and causes difficulties in sample selection.
Haoyu Wang   +8 more
doaj   +1 more source

Anomaly Detection and Localization With State‐of‐the‐Art Deep Learning Models to Support Quality Inspection in Car Manufacturing

open access: yesEngineering Reports, Volume 8, Issue 3, March 2026.
This work presents a deep learning framework for sealant inspection in automotive manufacturing, leveraging synthetic data to address the scarcity of real defects. Integrated with state‐of‐the‐art deep learning methods, the approach enhances anomaly detection and localization, demonstrating practical applicability and robustness under real‐world ...
Francesco Manigrasso   +3 more
wiley   +1 more source

The Arts Interview. Rae Perlin

open access: yes, 1985
Host Fred Hollingshurst interviews Newfoundland visual artist Rae Perlin. Perlin speaks about her life and her development as an artist.
Memorial University of Newfoundland.Educational Television Centre
core  

Algorithm for Visualizing Volumetric Pores and Wrinkles Based on a Displacement Map

open access: yesСовременные информационные технологии и IT-образование
The article proposes an approach to developing an algorithm for visualizing realistic skin micro-relief, focusing on the creation of volumetric pores and wrinkles.
Alexander Syryh, Sergei Medvedev
doaj   +1 more source

«Différant des Autres», Espacements et Temporalités Spectrales

open access: yesAnthropology of Consciousness, Volume 37, Issue 1, Spring 2026.
ABSTRACT That night that he agreed to our suggestion that we accompany him outside, for the whole night or until the overflow has passed, M seemed to be in direct contact with all the layers of astronomy, inhabiting all temporalities simultaneously. Outside, lying/sitting on the picnic table, in the pitch‐black darkness of the night in the woods, under
Amélie‐Anne Mailhot
wiley   +1 more source

A Reconstruction–Segmentation Framework for Robust Tree Cover Mapping in North Korea Using Time-Series Reconstruction Autoencoders

open access: yesRemote Sensing
Forests are a critical component of global carbon sequestration, biodiversity, and ecosystem services, making accurate mapping essential for long-term monitoring.
Hyun-Woo Jo, Youngjae Yoo, Seongwoo Jeon
doaj   +1 more source

A parametrically‐Conditioned Deep Learning Surrogate for Coherent Spinodal Decomposition

open access: yesAdvanced Theory and Simulations, Volume 9, Issue 2, February 2026.
Spinodal decomposition of strained alloys with cubic anisotropy is reproduced by a Convolutional Recurrent Neural Network, taking the misfit parameter as explicit input to return different morphologies. The predicted composition fields match phase‐field simulations over a broad range of parameters, allowing to reconstruct the full phase diagram.
Andrea Fantasia   +5 more
wiley   +1 more source

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