On-device research index

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.

169,051 papers · 148 categories

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5 results for “multitemporal”

Multisource and Multitemporal Data Fusion in Remote Sensingcs.LG

Combining diverse sensor data improves remote sensing analysis.

problem Heterogeneous remote sensing data poses challenges for effective processing.

method Multisource and multitemporal data fusion approaches.

result Improved performance of processing approaches through joint use of datasets.

remote sensing data fusion multisource multitemporal sensor data

2018-12-19abs ↗pdf ↗

Diffusion State Distances: Multitemporal Analysis, Fast Algorithms, and Applications to Biological Networksstat.ML

Develops DSD for analyzing multiscale biological networks.

problem Analyzing multiscale structure in biological networks.

method Data-driven diffusion process with multitemporal analysis.

result Parameter-free inference of intrinsic data structure.

Diffusion State Distance Multitemporal Analysis Biological Networks Data-Driven Metrics Multiscale Structure

2020-03-07abs ↗pdf ↗

Unsupervised Image Regression for Heterogeneous Change Detectioncs.CV

Unsupervised image regression detects changes in satellite images.

problem Detecting changes in heterogeneous multitemporal satellite images.

method Comparison of affinity matrices and image regression.

result Image regression improves change detection accuracy.

unsupervised learning image regression change detection heterogeneous data remote sensing

2019-09-07abs ↗pdf ↗

A Perspective on Gaussian Processes for Earth Observationcs.LG

Gaussian processes enhance EO with accurate and uncertain predictions.

problem Challenges in GP models for EO, including data-driven physics and causal inference.

method Data-driven physics-aware models respecting signal characteristics and physical laws.

result GP models need to evolve for better EO applications.

Gaussian processes Earth observation remote sensing uncertainty quantification physics-aware models

2020-07-02abs ↗pdf ↗

Estimating optical vegetation indices and biophysical variables for temperate forests with Sentinel-1 SAR data using machine learning techniques: A case study for Czechiastat.ML

Study uses SAR data to estimate forest vegetation indices, improving monitoring of temperate forests.

problem Limitations of optical satellite data in monitoring forest ecosystems, especially due to atmospheric effects.

method Estimating four vegetation indices (LAI, FAPAR, EVI, NDVI) using multitemporal Sentinel-1 SAR and ancillary data.

result Accurate estimation of forest vegetation indices using SAR data, achieving high

R^2

and low MAE values.

SAR data forest monitoring vegetation indices machine learning Sentinel-1

2023-11-13abs ↗pdf ↗