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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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5 results for “TOF”

Isotopic envelope identification by analysis of the spatial distribution of components in MALDI-MSI datastat.ML

Paper presents a method for identifying isotope envelopes in MALDI-ToF data.

problem Deisotoping of isotopic peaks in MALDI-ToF molecular imaging data.

method Uses Mamdani-Assilan fuzzy system and spatial maps of molecular distribution to identify isotope envelopes.

result Proposed method detects overlapping envelopes and analyzes large data sets.

MALDI-ToF isotope envelopes fuzzy system spatial maps peak pairs

2023-02-13abs ↗pdf ↗

Two-Stage Deep Learning for Accelerated 3D Time-of-Flight MRA without Matched Training Dataeess.IV

Deep learning for TOF-MRA without matched training data.

problem High-quality reconstruction from undersampled TOF-MRA.

method Two-stage unsupervised deep learning approach using cycleGAN theory.

result Exceeds performance of state-of-the-art CS-based methods.

deep learning TOF-MRA unsupervised cycleGAN compressed sensing

2020-08-04abs ↗pdf ↗

How to find a unicorn: a novel model-free, unsupervised anomaly detection method for time seriescs.LG

New algorithm detects unique events in time series data.

problem Detecting anomalous events in unknown properties.

method Model-free, unsupervised detection using Temporal Outlier Factor (TOF).

result TOF outperforms traditional outlier detection methods.

anomaly detection time series unique events TOF unicorn

2020-04-23abs ↗pdf ↗

How well do U-Net-based segmentation trained on adult cardiac magnetic resonance imaging data generalise to rare congenital heart diseases for surgical planning?eess.IV

Deep learning models trained on adult cardiac MRI data struggle to accurately segment rare congenital heart diseases.

problem Accuracy of U-Net-based segmentation models trained on adult cardiac MRI data when applied to rare congenital heart diseases like Tetralogy of Fallot.

method Cross-validation with four-fold, evaluation on unseen data from different pathologies.

result Deep learning models overfit to the training data, leading to significant accuracy drops when applied to other pathologies.

Deep Learning Cardiac MRI Segmentation Congenital Heart Disease Tetralogy of Fallot

2020-02-10abs ↗pdf ↗

Benchmark of structured machine learning methods for microbial identification from mass-spectrometry datastat.ML

Microbial identification is a central issue in microbiology, in particular in the fields of infectious diseases diagnosis and industrial quality control. The concept of species is tightly linked to the concept of biological and clinical classification where the proximity between species is generally measured in terms o…

2015-06-24abs ↗pdf ↗