Results 71 to 80 of about 42,095 (293)
Detail-Preserving Pooling in Deep Networks
, 2018 Most convolutional neural networks use some method for gradually downscaling the size of the hidden layers. This is commonly referred to as pooling, and is applied to reduce the number of parameters, improve invariance to certain distortions, and ...
Goesele, Michael +3 more
core +1 more source
Efficient dynamical downscaling of general circulation models using continuous data assimilation [PDF]
, 2019 Continuous data assimilation (CDA) is successfully implemented for the first time for efficient dynamical downscaling of a global atmospheric reanalysis.
Biswas A. +10 more
core +2 more sources
Unveil Fundamental Graph Properties for Neural Architecture Search
Advanced Science, EarlyView.This paper proposes NASGraph, a graph‐based framework that represents neural architectures as graphs whose structural properties determine performance. By revealing structure–performance relationships, NASGraph enables efficient neural architecture search with significantly reduced computation.
Zhenhan Huang +4 more
wiley +1 more source
Model performance of downscaling 1999-2004 hydrometeorological fields to the upper Rio Grande basin using different forcing datasets [PDF]
, 2008 This study downscaled more than five years of data (1999-2004) for hydrometeorological fields over the upper Rio Grande basin (URGB) to a 4-km resolution using a regional model [fifth-generation Pennsylvania State University-National Center for ...
Gao, X, Li, J, Sorooshian, S
core +1 more source
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
Advanced Science, EarlyView.Skeleton‐oriented object segmentation (SKOOTS) introduces a new strategy for 3D mitochondrial instance segmentation by predicting explicit skeletons rather than relying on boundary cues. This approach enables robust analysis of densely packed organelles in large FIB‐SEM datasets.
Christopher J. Buswinka +3 more
wiley +1 more source
Remote Sensing, 2023 Satellite precipitation data downscaling is gaining importance for climatic and hydrological studies at basin scale, especially in the data-scarce mountainous regions, e.g., the Upper Indus Basin (UIB).
Yixuan Wang +4 more
doaj +1 more source
Efficient Hybrid DCT-Domain Algorithm for Video Spatial Downscaling [PDF]
EURASIP Journal on Advances in Signal Processing, 2007 A highly efficient video downscaling algorithm for any arbitrary integer scaling factor performed in a hybrid pixel transform domain is proposed. This algorithm receives the encoded DCT coefficient blocks of the input video sequence and efficiently computes the DCT coefficients of the scaled video stream.
Roma Nuno, Sousa Leonel
openaire +3 more sources
Downscaling of fracture energy during brittle creep experiments [PDF]
, 2011 We present mode 1 brittle creep fracture experiments along fracture surfaces that contain strength heterogeneities. Our observations provide a link between smooth macroscopic time-dependent failure and intermittent microscopic stress-dependent processes.
Ampuero, J.-P. +5 more
core +4 more sources
Advanced Science, EarlyView.ABSTRACT Strain is a proven technique for modifying the bandgap and enhancing carrier mobility in 2D materials. Most current strain engineering techniques rely on the post‐growth transfer of these atomically thin materials from growth substrates to target surfaces, limiting their integration into nanoelectronics.
Berke Erbas +8 more
wiley +1 more source