Results 21 to 30 of about 20,444,531 (305)
VoxGRAF: Fast 3D-Aware Image Synthesis with Sparse Voxel Grids [PDF]
Neural Information Processing Systems, 2022 State-of-the-art 3D-aware generative models rely on coordinate-based MLPs to parameterize 3D radiance fields. While demonstrating impressive results, querying an MLP for every sample along each ray leads to slow rendering.
K. Schwarz +4 more
semanticscholar +1 more source
Flash-Based Computing-in-Memory Architecture to Implement High-Precision Sparse Coding
Micromachines, 2023 To address the concerns with power consumption and processing efficiency in big-size data processing, sparse coding in computing-in-memory (CIM) architectures is gaining much more attention.
Yueran Qi +9 more
doaj +1 more source
Sparse and spurious: dictionary learning with noise and outliers [PDF]
, 2015 A popular approach within the signal processing and machine learning communities consists in modelling signals as sparse linear combinations of atoms selected from a learned dictionary.
Bach, Francis +2 more
core +5 more sources
Sparse model identification using a forward orthogonal regression algorithm aided by mutual information [PDF]
, 2006 A sparse representation, with satisfactory approximation accuracy, is usually desirable in any nonlinear system identification and signal processing problem.
Billings, S.A., Wei, H.L.
core +2 more sources
Efficient Sparse Processing in Smart Home Applications
SenSys-ML, 2019 In recent years, smart home technology has become prevalant and important for various applications. A typical smart home system consists of sensing nodes sending raw data to a cloud server which performs inference using a Machine Learning (ML) model ...
Rishikanth Chandrasekaran +6 more
semanticscholar +1 more source
Sparse Instance Activation for Real-Time Instance Segmentation [PDF]
Computer Vision and Pattern Recognition, 2022 In this paper, we propose a conceptually novel, efficient, and fully convolutional framework for real-time instance segmentation. Previously, most instance segmentation methods heavily rely on object detection and perform mask prediction based on ...
Tianheng Cheng +7 more
semanticscholar +1 more source
Sparse Principal Component Analysis for Natural Language Processing
Annals of Data Science, 2020 High dimensional data are rapidly growing in many different disciplines, particularly in natural language processing. The analysis of natural language processing requires working with high dimensional matrices of word embeddings obtained from text data ...
Reza Drikvandi, Olamide O. Lawal
semanticscholar +1 more source
RSNN: A Software/Hardware Co-Optimized Framework for Sparse Convolutional Neural Networks on FPGAs
IEEE Access, 2021 Convolutional Neural Networks (CNNs) have been shown to be very useful in image recognition and other Artificial Intelligence (AI) applications, however, at the expense of intensive computation requirement.
Weijie You, Chang Wu
doaj +1 more source
MMSE Estimation of Sparse Lévy Processes [PDF]
IEEE Transactions on Signal Processing, 2013 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
U.S. Kamilov, P. Pad, A. Amini, M. Unser
openaire +1 more source
PLoS ONE, 2022 In the compressed processing of hyperspectral images, orthogonal matching pursuit algorithm (OMP) can be used to obtain sparse decomposition results.
Li Wang, Wei Wang
doaj +1 more source