Results 91 to 100 of about 109,140 (374)
Photonic Hybrid Integration: Strategies and Promises of Advanced Additive Manufacturing
Advanced Optical Materials, EarlyView.Heterogeneous photonic integration combines wafer bonding, transfer printing, and advanced multi‐photon lithography to realize compact, adaptable photonic systems. This review highlights breakthroughs in hybrid materials, metrology, and 4D printing, revealing how the convergence of traditional and emerging fabrication unlocks scalable, high‐performance
Zhitian Shi +3 more
wiley +1 more source
ThumbNet: One Thumbnail Image Contains All You Need for Recognition
, 2020 Although deep convolutional neural networks (CNNs) have achieved great success in computer vision tasks, its real-world application is still impeded by its voracious demand of computational resources.
Abadi Mart'in +11 more
core +1 more source
Remote Sensing, 2021 High-spatial-resolution precipitation data are of great significance in many applications, such as ecology, hydrology, and meteorology. Acquiring high-precision and high-resolution precipitation data in a large area is still a great challenge.
Xin Yan +5 more
semanticscholar +1 more source
On–Off Switchable Micromotors for Use in Steerable Microvehicles
Advanced Robotics Research, EarlyView.Electrically controllable micromotors and microvehicles are developed by tuning the diffusion of the fuel. Self‐propelled micromotors using bubble propulsion show great promise for miniaturized devices with multiuse purposes such as cargo delivery and sensing. However, there is currently no method to electrically switch the micromotors on or off. Here,
Hugo Severinsson +3 more
wiley +1 more source
The Interaction Between PDE and Graphs in Multiscale Modeling
, 2016 In this article an upscaled model is presented, for complex networks with highly clustered regions exchanging some abstract quantities in both, microscale and macroscale level.
Morales, Fernando A +1 more
core +2 more sources
A frailty-contagion model for multi-site hourly precipitation driven by atmospheric covariates [PDF]
, 2014 Accurate stochastic simulations of hourly precipitation are needed for impact studies at local spatial scales. Statistically, hourly precipitation data represent a difficult challenge.
Koch, Erwan, Naveau, Philippe
core +2 more sources
Formation of Condition‐Dependent Alpha‐Synuclein Fibril Strain in Artificial Cerebrospinal Fluid
Advanced Science, EarlyView.α‐synuclein aggregation in artificial cerebrospinal fluid (aCSF) leads to a distinct conformation with an electron density pocket motif found in aggregates from PD and MSA patients. Such fibrils has low stability outside the reaction conditions, hinting about the influence of cerebrospinal fluid components not only on the formation, but also on the ...
Rūta Sniečkutė +7 more
wiley +1 more source
A Lightweight Terrain‐Constraint Model for Wind Spatial Downscaling
Journal of Geophysical Research: Machine Learning and ComputationHigh‐resolution wind fields has always been the goal of refined meteorological forecasting. Using advanced deep learning algorithms for wind downscaling is an effective approach to achieve this goal. However, the lack of physical process understanding in
Anboyu Guo +9 more
doaj +1 more source
Temporal stability of soil moisture and radar backscatter observed by the advanced Synthetic Aperture Radar (ASAR) [PDF]
, 2008 The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics.
Alexander Löw +58 more
core +4 more sources
Configuration and intercomparison of deep learning neural models for statistical downscaling
Geoscientific Model Development, 2019 . Deep learning techniques (in particular convolutional neural networks, CNNs) have recently emerged as a promising approach for statistical downscaling due to their ability to learn spatial features from huge spatiotemporal datasets.
J. Baño-Medina +2 more
semanticscholar +1 more source