Tootfinder

Comparative study of Wavelet transform and Fourier domain filtering for medical image denoising
M. Ali Saif, Bassam M. Mughalles, Ibrahim G. H. Loqman
https://arxiv.org/abs/2509.26608

Comparative study of Wavelet transform and Fourier domain filtering for medical image denoising
Denoising of images is a crucial preprocessing step in medical imaging, essential for improving diagnostic clarity. While deep learning methods offer state-of-the-art performance, their computational complexity and data requirements can be prohibitive. In this study we present a comprehensive comparative analysis of two classical, computationally efficient transform-domain techniques: Discrete Wavelet Transform (DWT) and Discrete Fourier Cosine Transform (DFCT) filtering. We evaluated their eff…

"As the planet warmed, politics wobbled: The defining climate moments of 2025"
#Climate #ClimateChange

How 2025 became one of the hottest and most divisive climate years
Record warming met weak political resolve as climate pressures mounted this year.

Did I go a little extra with leftovers breakfast? Yeah, why not?
Pork, fluffy egg, waffled stuffing, homemade gravy (didn’t get any in my leftovers)

A Submillisecond Fourier and Wavelet-based Model to Extract Variable Candidates from the #NEOWISE Single-exposure Database: https://iopscience.iop.org/article/10.3847/1538-3881/ad7fe6 -> xeet about the very young author: https://x.com/MAstronomers/status/2004334592908505508 -> reaction by the new NASA Administrator: https://x.com/rookisaacman/status/2004772750494499104

Geef input aan het ministerie van landbouw etc. Denk mee over het nieuwe GLB - Wevaluate
https://toekomst-glb.raadpleging.net/

google_web: Old Google web graph (2002)
A web graph representing a crawl of a portion of the general WWW, from a 2002 Google Programming contest.
This network has 916428 nodes and 5105039 edges.
Tags: Informational, Web graph, Unweighted
https://networks.skewed.de/net/google_web<…

Investigating the Impact of Rational Dilated Wavelet Transform on Motor Imagery EEG Decoding with Deep Learning Models
Marco Siino, Giuseppe Bonomo, Rosario Sorbello, Ilenia Tinnirello
https://arxiv.org/abs/2510.09242

Investigating the Impact of Rational Dilated Wavelet Transform on Motor Imagery EEG Decoding with Deep Learning Models
The present study investigates the impact of the Rational Discrete Wavelet Transform (RDWT), used as a plug-in preprocessing step for motor imagery electroencephalographic (EEG) decoding prior to applying deep learning classifiers. A systematic paired evaluation (with/without RDWT) is conducted on four state-of-the-art deep learning architectures: EEGNet, ShallowConvNet, MBEEG\_SENet, and EEGTCNet. This evaluation was carried out across three benchmark datasets: High Gamma, BCI-IV-2a, and BCI-I…

Time-causal and time-recursive wavelets
Tony Lindeberg
https://arxiv.org/abs/2510.05834 https://arxiv.org/pdf/2510.05834

Time-causal and time-recursive wavelets
When to apply wavelet analysis to real-time temporal signals, where the future cannot be accessed, it is essential to base all the steps in the signal processing pipeline on computational mechanisms that are truly time-causal. This paper describes how a time-causal wavelet analysis can be performed based on concepts developed in the area of temporal scale-space theory, originating from a complete classification of temporal smoothing kernels that guarantee non-creation of new structures from f…

Secret-Key Agreement Through Hidden Markov Modeling of Wavelet Scattering Embeddings
Nora Basha, Bechir Hamdaoui, Attila A. Yavuz, Thang Hoang, Mehran Mozaffari Kermani
https://arxiv.org/abs/2510.09773

Secret-Key Agreement Through Hidden Markov Modeling of Wavelet Scattering Embeddings
Secret-key generation and agreement based on wireless channel reciprocity offers a promising avenue for securing IoT networks. However, existing approaches predominantly rely on the similarity of instantaneous channel measurement samples between communicating devices. This narrow view of reciprocity is often impractical, as it is highly susceptible to noise, asynchronous sampling, channel fading, and other system-level imperfections -- all of which significantly impair key generation performanc…

google_web: Old Google web graph (2002)
A web graph representing a crawl of a portion of the general WWW, from a 2002 Google Programming contest.
This network has 916428 nodes and 5105039 edges.
Tags: Informational, Web graph, Unweighted
https://networks.skewed.de/net/google_web<…