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A lot of work has been done to reach the best possible performance of predictive models on images. There are fewer studies about the resilience of these models when they are trained on image datasets that suffer modifications altering their…

Computer Vision and Pattern Recognition · Computer Science 2023-01-19 Pau Gallés , Katalin Takats , Javier Marin

We present a theoretical evaluation of radiation dose constraints for extreme ultraviolet (EUV) and soft X-ray microscopy. Our work particularly addresses the long-standing concern regarding strong absorption of EUV radiation in biological…

Applied Physics · Physics 2026-05-29 Chang Liu , Leona Licht , Jan Rothhardt

The observing strategy of a galaxy survey influences the degree to which its resulting data can be used to accomplish any science goal. LSST is thus seeking metrics of observing strategies for multiple science cases in order to optimally…

Instrumentation and Methods for Astrophysics · Physics 2021-04-19 Alex I. Malz , François Lanusse , John Franklin Crenshaw , Melissa L. Graham

By sending one or more telescopes into space, Space-VLBI (SVLBI) is able to achieve even higher angular resolution and is therefore the trend of the VLBI technique. For SVLBI program, the design of satellite orbits plays an important role…

Instrumentation and Methods for Astrophysics · Physics 2021-03-31 Lei Liu , Weimin Zheng

Context. Gravitational lensing is one of the leading tools in understanding the dark side of the Universe. The need for accurate, efficient and effective methods which are able to extract this information along with other cosmological…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-03 Marika Asgari , Peter Schneider , Patrick Simon

The subject of this research is the development of an intelligent, integrated framework for the automated inspection of photovoltaic (PV) infrastructure that addresses the critical shortcomings of conventional methods, including thermal…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Andrii Lysyi , Anatoliy Sachenko , Pavlo Radiuk , Mykola Lysyi , Oleksandr Melnychenko , Diana Zahorodnia

Error-bounded lossy compression is one of the most efficient solutions to reduce the volume of scientific data. For lossy compression, progressive decompression and random-access decompression are critical features that enable on-demand…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-09-03 Daoce Wang , Pascal Grosset , Jesus Pulido , Jiannan Tian , Tushar M. Athawale , Jinda Jia , Baixi Sun , Boyuan Zhang , Sian Jin , Kai Zhao , James Ahrens , Fengguang Song

The complex structure and extensive details of solar spectral data, combined with a recent surge in volume, present significant processing challenges. To address this, we propose a deep learning-based compression technique using deep…

Machine Learning · Computer Science 2025-02-10 Jargalmaa Batmunkh , Yusuke Iida , Takayoshi Oba , Haruhisa Iijima

Modern galaxy surveys produce redshift probability density functions (PDFs) in addition to traditional photometric redshift (photo-$z$) point estimates. However, the storage of photo-$z$ PDFs may present a challenge with increasingly large…

Instrumentation and Methods for Astrophysics · Physics 2021-08-03 A. I. Malz , P. J. Marshall , S. J. Schmidt , M. L. Graham , J. DeRose , R. Wechsler

Scientific data reduction on-board deep space missions is a powerful approach to maximise science return, in the absence of wide telemetry bandwidths. The Polarimetric and Helioseismic Imager (PHI) on-board the Solar Orbiter (SO) is the…

Photometric redshifts are a key tool to extract as much information as possible from planned cosmic shear experiments. In this work we aim to test the performances that can be achieved with observations in the near-infrared from space and…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-03 Fabio Bellagamba , Massimo Meneghetti , Lauro Moscardini , Micol Bolzonella

Super resolution offers a way to harness medium even lowresolution but historically valuable remote sensing image archives. Generative models, especially diffusion models, have recently been applied to remote sensing super resolution…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Songxi Yang , Tang Sui , Qunying Huang

Context. Several upcoming and proposed space missions, such as Solar Orbiter, will be limited in telemetry and thus require data compression. Aims. We test the impact of data compression on local correlation tracking (LCT) of time-series of…

Solar and Stellar Astrophysics · Physics 2016-02-17 Björn Löptien , Aaron C. Birch , Tom L. Duvall , Laurent Gizon , Jesper Schou

The Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) returns high-resolution images of the solar atmosphere in seven extreme ultraviolet (EUV) wavelength channels. The images are processed on the ground to…

Solar and Stellar Astrophysics · Physics 2022-01-05 Peter R. Young , Nicholeen M. Viall , Michael S. Kirk , Emily I. Mason , Lakshmi Pradeep Chitta

The EUV Imaging Spectrometer (EIS) on the Hinode satellite is capable of measuring emission line center positions for Gaussian line profiles to a fraction of a spectral pixel, resulting in relative solar Doppler-shift measurements with an…

The Atmospheric Imaging Assembly (AIA) and the Exteme-ultraviolet Variability Experiment (EVE) onboard the Solar Dynamics Observatory include spectral windows in the X-ray/EUV band. Accuracy and completeness of the atomic data in this…

Solar and Stellar Astrophysics · Physics 2015-05-30 Paola Testa , Jeremy J. Drake , Enrico Landi

The rapid expansion of computational capabilities and the ever-growing scale of modern HPC systems present formidable challenges in managing exascale scientific data. Faced with such vast datasets, traditional lossless compression…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-04-23 Wenqi Jia , Sian Jin , Jinzhen Wang , Wei Niu , Dingwen Tao , Miao Yin

Many scientific investigations of photometric galaxy surveys require redshift estimates, whose uncertainty properties are best encapsulated by photometric redshift (photo-z) posterior probability density functions (PDFs). A plethora of…

The analysis of weak gravitational lensing in wide-field imaging surveys is considered to be a major cosmological probe of dark energy. Our capacity to constrain the dark energy equation of state relies on the accurate knowledge of the…

Cosmology and Nongalactic Astrophysics · Physics 2021-03-24 Euclid Collaboration , O. Ilbert , S. de la Torre , N. Martinet , A. H. Wright , S. Paltani , C. Laigle , I. Davidzon , E. Jullo , H. Hildebrandt , D. C. Masters , A. Amara , C. J. Conselice , S. Andreon , N. Auricchio , R. Azzollini , C. Baccigalupi , A. Balaguera-Antolínez , M. Baldi , A. Balestra , S. Bardelli , R. Bender , A. Biviano , C. Bodendorf , D. Bonino , S. Borgani , A. Boucaud , E. Bozzo , E. Branchini , M. Brescia , C. Burigana , R. Cabanac , S. Camera , V. Capobianco , A. Cappi , C. Carbone , J. Carretero , C. S. Carvalho , S. Casas , F. J. Castander , M. Castellano , G. Castignani , S. Cavuoti , A. Cimatti , R. Cledassou , C. Colodro-Conde , G. Congedo , L. Conversi , Y. Copin , L. Corcione , A. Costille , J. Coupon , H. M. Courtois , M. Cropper , J. Cuby , A. Da Silva , H. Degaudenzi , D. Di Ferdinando , F. Dubath , C. Duncan , X. Dupac , S. Dusini , A. Ealet , M. Fabricius , S. Farrens , P. G. Ferreira , F. Finelli , P. Fosalba , S. Fotopoulou , E. Franceschi , P. Franzetti , S. Galeotta , B. Garilli , W. Gillard , B. Gillis , C. Giocoli , G. Gozaliasl , J. Graciá-Carpio , F. Grupp , L. Guzzo , S. V. H. Haugan , W. Holmes , F. Hormuth , K. Jahnke , E. Keihanen , S. Kermiche , A. Kiessling , C. C. Kirkpatrick , M. Kunz , H. Kurki-Suonio , S. Ligori , P. B. Lilje , I. Lloro , D. Maino , E. Maiorano , O. Marggraf , K. Markovic , F. Marulli , R. Massey , M. Maturi , N. Mauri , S. Maurogordato , H. J. McCracken , E. Medinaceli , S. Mei , R. Benton Metcalf , M. Moresco , B. Morin , L. Moscardini , E. Munari , R. Nakajima , C. Neissner , S. Niemi , J. Nightingale , C. Padilla , F. Pasian , L. Patrizii , K. Pedersen , R. Pello , V. Pettorino , S. Pires , G. Polenta , M. Poncet , L. Popa , D. Potter , L. Pozzetti , F. Raison , A. Renzi , J. Rhodes , G. Riccio , E. Romelli , M. Roncarelli , E. Rossetti , R. Saglia , A. G. Sánchez , D. Sapone , P. Schneider , T. Schrabback , V. Scottez , A. Secroun , G. Seidel , S. Serrano , C. Sirignano , G. Sirri , L. Stanco , F. Sureau , P. Tallada Crespí , M. Tenti , H. I. Teplitz , I. Tereno , R. Toledo-Moreo , F. Torradeflot , A. Tramacere , E. A. Valentijn , L. Valenziano , J. Valiviita , T. Vassallo , Y. Wang , N. Welikala , J. Weller , L. Whittaker , A. Zacchei , G. Zamorani , J. Zoubian , E. Zucca

Lossless compression is essential for efficient data storage and transmission. Although learning-based lossless compressors achieve strong results, most of them are designed for a single modality, leading to redundant compressor deployments…

Machine Learning · Computer Science 2026-03-03 Yan Zhao , Zhengxue Cheng , Junxuan Zhang , Dajiang Zhou , Qunshan Gu , Qi Wang , Li Song