Tootfinder

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

QWD-GAN: Quality-aware Wavelet-driven GAN for Unsupervised Medical Microscopy Images Denoising
Qijun Yang, Yating Huang, Lintao Xiang, Hujun Yin
https://arxiv.org/abs/2509.15814

QWD-GAN: Quality-aware Wavelet-driven GAN for Unsupervised Medical Microscopy Images Denoising
Image denoising plays a critical role in biomedical and microscopy imaging, especially when acquiring wide-field fluorescence-stained images. This task faces challenges in multiple fronts, including limitations in image acquisition conditions, complex noise types, algorithm adaptability, and clinical application demands. Although many deep learning-based denoising techniques have demonstrated promising results, further improvements are needed in preserving image details, enhancing algorithmic e…

On the convergence rate in the central limit theorem for linearly extended negative quadrant dependent random variables and its applications
Mohamed Kaber El Alem, Zohra Guessoum, Abdelkader Tatachak, Ourida Sadki
https://arxiv.org/abs/2509.15353

On the convergence rate in the central limit theorem for linearly extended negative quadrant dependent random variables and its applications
In this paper, we establish the convergence rate in central limit theorem (CLT) for linearly extended negative quadrant dependent (LENQD) random variables (rv's). Under some weak conditions, the rate of normal approximation is shown as $O(n^{-1/9})$. As an application, the convergence rate in CLT of the wavelet estimator for the nonparametric regression model with LENQD errors is presented as $O(n^{-1/9})$. The performance of the main results is illustrated through a simulation study based on a…

DPC-QA Net: A No-Reference Dual-Stream Perceptual and Cellular Quality Assessment Network for Histopathology Images
Qijun Yang, Boyang Wang, Hujun Yin
https://arxiv.org/abs/2509.15802

DPC-QA Net: A No-Reference Dual-Stream Perceptual and Cellular Quality Assessment Network for Histopathology Images
Reliable whole slide imaging (WSI) hinges on image quality,yet staining artefacts, defocus, and cellular degradations are common. We present DPC-QA Net, a no-reference dual-stream network that couples wavelet-based global difference perception with cellular quality assessment from nuclear and membrane embeddings via an Aggr-RWKV module. Cross-attention fusion and multi-term losses align perceptual and cellular cues. Across different datasets, our model detects staining, membrane, and nuclear is…

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…

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…

🇺🇦 #NowPlaying on #BBC6Music's #CraigCharles
Green Lung:
🎵 Maxine (Witch Queen)
#GreenLung
https://greenlung.bandcamp.com/track/maxine-witch-queen
https://open.spotify.com/track/2wbfb2aLoDZMfX3kuuqYbt

LR-WaveHoltz: A Low-Rank Helmholtz Solver
Andreas Granath, Daniel Appel\"o, Siyang Wang
https://arxiv.org/abs/2510.09352 https://arxiv.org/pdf/2510.09…

LR-WaveHoltz: A Low-Rank Helmholtz Solver
We propose a low-rank method for solving the Helmholtz equation. Our approach is based on the WaveHoltz method, which computes Helmholtz solutions by applying a time-domain filter to the solution of a related wave equation. The wave equation is discretized by high-order multiblock summation-by-parts finite differences. In two dimensions we use the singular value decomposition and in three dimensions we use tensor trains to compress the numerical solution. To control rank growth we use step-trun…

🇺🇦 #NowPlaying on #BBC6Music's #FreakZonePlaylist
Loren Mazzacane Connors & Suzanne Langille:
🎵 Evangeline
#LorenMazzacaneConnors #SuzanneLangille
https://open.spotify.com/track/0wvlTbjwaPhyOWuFGm6fYG