Results 31 to 40 of about 53,402 (265)
DANAE++: A Smart Approach for Denoising Underwater Attitude Estimation
Sensors, 2021 One of the main issues for the navigation of underwater robots consists in accurate vehicle positioning, which heavily depends on the orientation estimation phase.
Paolo Russo +2 more
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Sensors, 2022 Maintenance scheduling is a fundamental element in industry, where excessive downtime can lead to considerable economic losses. Active monitoring systems of various components are ever more used, and rolling bearings can be identified as one of the ...
Eugenio Brusa +3 more
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Similarity and denoising [PDF]
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2013 We can discover the effective similarity among pairs of finite objects and denoise a finite object using the Kolmogorov complexity of these objects. The drawback is that the Kolmogorov complexity is not computable. If we approximate it, using a good real-world compressor, then it turns out that on natural data the processes give adequate results in ...
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Modified non-local means: A novel denoising approach to process gravity field data
Open Geosciences, 2023 Gravity measurement is a basic geophysical method for non-destructive exploration of mineral resources and hydrocarbons and also for geological studies. The quality of gravity data measured is constantly degraded by a low signal-to-noise ratio.
Ai Hanbing +6 more
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New Denoising Method for Lidar Signal by the WT-VMD Joint Algorithm
Sensors, 2022 Light detection and ranging (LIDAR) is an active remote sensing system. Lidar echo signal is non-linear and non-stationary, which is often accompanied by various noises.
Zhenzhu Wang +3 more
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Latent Diffusion Process With Mechanistic Guidance For Designing Functionally Graded Metamaterials With Perfect Connectivity. [PDF]
Adv Sci (Weinh)A latent diffusionâbased framework is proposed for designing functionally graded metamaterials with perfect connectivity. By integrating vectorâquantized latent representations with mechanistic guidance, the framework enables accurate inverse design toward target elastic properties.
Yu J, Lee D, Kim N.
europepmc +2 more sources
Composite Denoising Autoencoders [PDF]
, 2016 In representation learning, it is often desirable to learn features at different levels of scale. For example, in image data, some edges will span only a few pixels, whereas others will span a large portion of the image. We introduce an unsupervised representation learning method called a composite denoising autoencoder CDA to address this.
Geras, Krzysztof, Sutton, Charles
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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.
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Supervised Neural Discrete Universal Denoiser for Adaptive Denoising
CoRR, 2021 Preprint
Sungmin Cha +3 more
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Medical Image Denoising Using Convolutional Denoising Autoencoders [PDF]
2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW), 2016 To appear: 6 pages, paper to be published at the Fourth Workshop on Data Mining in Biomedical Informatics and Healthcare at ICDM ...
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