Results 61 to 70 of about 259,715 (355)
Sensors, 2019 In this paper, a novel hybrid method combining adaptive chirp mode pursuit (ACMP) with an adaptive multiscale Savitzky−Golay filter (AMSGF) based on adaptive moving average (AMA) is proposed for offline denoising micro-electromechanical system ...
Jingjing He, Changku Sun, Peng Wang
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Robust Preference-Guided Denoising for Graph based Social Recommendation [PDF]
The Web Conference, 2023 Graph Neural Network (GNN) based social recommendation models improve the prediction accuracy of user preference by leveraging GNN in exploiting preference similarity contained in social relations.
Yuhan Quan +5 more
semanticscholar +1 more source
A Hybrid Algorithm for Noise Suppression of MEMS Accelerometer Based on the Improved VMD and TFPF
Micromachines, 2022 High-G MEMS accelerometer (HGMA) is a new type of sensor; it has been widely used in high precision measurement and control fields. Inevitably, the accelerometer output signal contains random noise caused by the accelerometer itself, the hardware circuit
Yongjun Zhou, Huiliang Cao, Tao Guo
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Adaptive Image Denoising by Targeted Databases [PDF]
, 2014 We propose a data-dependent denoising procedure to restore noisy images. Different from existing denoising algorithms which search for patches from either the noisy image or a generic database, the new algorithm finds patches from a database that ...
Enming Luo +3 more
core +1 more source
Deep Orthogonal Transform Feature for Image Denoising
IEEE Access, 2020 Recently, CNN-based image denoising has been investigated and shows better performance than conventional vision based techniques. However, there are still a couple of limits that are weak partly in restoring image details like textured regions or produce
Yoon-Ho Shin +3 more
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Research on microseismic denoising method based on CBDNet
Artificial Intelligence in Geosciences, 2023 Noise suppression is an important part of microseismic monitoring technology. Signal and noise can be separated by denoising and filtering to improve the subsequent analysis.
Jianchao Lin +3 more
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Denoising as well as the best of any two denoisers [PDF]
2013 IEEE International Symposium on Information Theory, 2013 Given two arbitrary sequences of denoisers for block lengths tending to infinity we ask if it is possible to construct a third sequence of denoisers with an asymptotically vanishing (in block length) excess expected loss relative to the best expected loss of the two given denoisers for all clean channel input sequences.
openaire +3 more sources
Discrete Denoising With Shifts [PDF]
IEEE Transactions on Information Theory, 2009 We introduce S-DUDE, a new algorithm for denoising DMC-corrupted data. The algorithm, which generalizes the recently introduced DUDE (Discrete Universal DEnoiser) of Weissman et al., aims to compete with a genie that has access, in addition to the noisy data, also to the underlying clean data, and can choose to switch, up to $m$ times, between sliding ...
Taesup Moon, Tsachy Weissman
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MoFusion: A Framework for Denoising-Diffusion-Based Motion Synthesis [PDF]
Computer Vision and Pattern Recognition, 2022 Conventional methods for human motion synthesis have either been deterministic or have had to struggle with the trade-off between motion diversity vs motion quality. In response to these limitations, we introduce MoFusion, i.e., a new denoising-diffusion-
Rishabh Dabral +3 more
semanticscholar +1 more source
Applied Sciences, 2022 Supervised image denoising methods based on deep neural networks require a large amount of noisy-clean or noisy image pairs for network training. Thus, their performance drops drastically when the given noisy image is significantly different from the ...
Shaoping Xu +5 more
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