Davy, A.[Axel]
* 2018: Reducing Anomaly Detection in Images to Detection in Noise
* 2019: Detection of Small Anomalies on Moving Background
* 2019: How to Reduce Anomaly Detection in Images to Anomaly Detection in Noise
* 2019: Image Anomalies: A Review and Synthesis of Detection Methods
* 2019: Joint Demosaicking and Denoising by Fine-Tuning of Bursts of Raw Images
* 2019: Model-Blind Video Denoising via Frame-To-Frame Training
* 2019: Non-Local CNN for Video Denoising, A
* 2019: Optimization of Image B-spline Interpolation for GPU Architectures
* 2021: Fast, Nonlocal and Neural: A Lightweight High Quality Solution to Image Denoising
* 2021: Self-supervised multi-image super-resolution for push-frame satellite images
* 2021: Self-supervised training for blind multi-frame video denoising
* 2022: Self-Supervised Super-Resolution for Multi-Exposure Push-Frame Satellites
* 2023: Improving Pixel-Level Contrastive Learning by Leveraging Exogenous Depth Information
* 2023: L1BSR: Exploiting Detector Overlap for Self-Supervised Single-Image Super-Resolution of Sentinel-2 L1B Imagery
* 2024: Fixed Pattern Noise Removal for Multi-View Single-Sensor Infrared Camera
* 2024: On the Importance of Large Objects in CNN Based Object Detection Algorithms
Includes: Davy, A.[Axel] Davy, A.
16 for Davy, A.
Davy, M.
* 2002: Optimized support vector machines for nonstationary signal classification
* 2006: Abrupt Change Detection Algorithm for Buried Landmines Localization, An
* 2007: Improved one-class SVM classifier for sounds classification
* 2010: Generative Supervised Classification Using Dirichlet Process Priors
Includes: Davy, M. Davy, M.[Manuel]
Davydov, A.[Andrey]
* 2022: Adversarial Parametric Pose Prior
* 2023: Remote Seismoacoustic Monitoring of Tropical Cyclones in the Sea of Japan
Includes: Davydov, A.[Andrey] Davydov, A.[Aleksandr]
Davydov, S.P.[Sergey P.]
* 2018: Vegetation Indices Do Not Capture Forest Cover Variation in Upland Siberian Larch Forests
Davydow, A.
* 2018: Building Detection from Satellite Imagery Using a Composite Loss Function
* 2018: Land Cover Classification from Satellite Imagery with U-Net and Lovász-Softmax Loss
* 2018: Land Cover Classification with Superpixels and Jaccard Index Post-Optimization