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Proceedings of the Thirteenth Indian conference on Computer Vision, Graphics and Image processing

作者： Suresh Nehra Jayanta Laha J. Mukhopadhyay P. K. Biswas Indian Institute of Technology Kharagpur India Indian Space Research Organisation India

ISBN: (纸本)9781450398220

Light field imaging has emerged as a new modality, enabling to capture the angular and spatial information of a scene. This additional angular information is used to estimate the depth of a 3-D scene. The continuum of virtual view-points in light field data efficiently handles occlusion and provides a robust depth estimate for smaller distances. However, a narrow baseline in a light field camera limits the depth estimation for larger distances. To have an efficient occlusion handling and increase the operating distances, we proposed a novel disparity based stereo light field depth estimation method. First, segments are obtained in central sub-aperture of left view and then estimate the disparity vector of these segments using left camera sub-aperture images. This handles occlusion efficiently. Then stereo disparity at boundaries of these segments exploiting the epipolar geometry inherent in a light field data. Finally this stereo disparity at boundaries is propagated to other pixels and normalized. We provided a synthetic stereo light field data-set having inherent characteristic of a light field. We have tested our approach on a variety of real-world scenes captured with Lytro Illum camera and also on synthetic images. The proposed method outperforms several state-of-the-art algorithms.

关键词： stereo light field stereo depth estimation. Lytro Illum Light Field Imaging

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The Stereo Event Builder software system of the ASTRI Mini-Array 38

The Stereo Event Builder software system of the ASTRI Mini-A...

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38th International Cosmic Ray conference, ICRC 2023

作者： Germani, S. Lombardi, S. La Parola, V. Lucarelli, F. Saturni, F.G. Bigongiari, C. Cardillo, M. Mineo, T. Mastropietro, M. Università degli Studi di Perugia Dipartimento di Fisica e Geologia Via A. Pascoli Perugia06123 Italy INAF - Osservatorio Astronomico di Roma Via Frascati 33 Monte Porzio CatoneI-00078 Italy ASI - Space Science Data Center Via del Politecnico s.n.c. RomeI-00133 Italy INAF - Istituto di Astrofisica Spaziale e Fisica Cosmica via Ugo La Malfa 153 Palermo90146 Italy INAF - Istituto di Astrofisica e Planetologia Spaziali Via del Fosso del Cavaliere 100 Roma00133 Italy

The Stereo Event Builder (SEB) software system of the ASTRI Mini-Array is the part of the off-line data processing chain that is responsible for identifying single and stereo Cherenkov events. The ASTRI Mini-Array is an international project led by the Italian National Institute for Astrophysics (INAF) which is in the process of deploying nine Imaging Atmospheric Cherenkov Telescopes (IACTs) of the 4-m class at the Observatorio del Teide in Tenerife (Spain). The project is designed to detect very high-energy gamma rays up to the multi-TeV scale. In the ASTRI Mini-Array operation concept, the expected performance is based on the stereoscopic technique, i.e. the detection of the same atmospheric shower event with two or more telescopes. However all single-telescope events are acquired independently and stored for off-line processing. This strong requirement must meet the need to observe muon events with each single telescope to allow for calibrations. In this scenario, the correct identification of the single telescope triggers participating to the same stereo event is of fundamental importance. In this contribution we present the SEB constraints, design, and expected performance. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmology

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Modeling of recovery efficiency of sampling devices used in planetary protection bioburden estimation

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APPLIED AND ENVIRONMENTAL MICROBIOLOGY 2023年第12期89卷 e00832-23-e00832-23页

作者： Dinicola, Michael Seuylemezian, Arman Guan, Lisa Moissl-Eichinger, Christine Baker, Amy Johns, Jason CALTECH Jet Prop Lab Pasadena CA 91125 USA Med Univ Graz Diagnost & Res Inst Hyg Microbiol & Environm Med Graz Austria SETI Inst Mountain View CA USA Kennedy Space Ctr Herndon Solut Grp Merritt Isl FL USA

Planetary protection is a discipline dedicated to preventing biological contamination between celestial bodies and Earth during space exploration to ensure the integrity of scientific research. National space agencies such as the National Aeronautics and space Administration and the european space Agency set biological cleanliness requirements for their missions based on the guidelines provided in The Committee on space Research's Planetary Protection Policy. Compliance with these requirements is often demonstrated by surface sampling of spacecraft hardware and associated surfaces to enumerate the number of microorganisms present and establish that they are below the required level. The discipline has employed a variety of tools to perform sampling;the recovery efficiency of which is a key parameter used to generate spacecraft level cleanliness estimates. In this study, we investigated how recovery efficiency differs by inoculum amount and species. This was analyzed across different sampling devices using a set of microorganisms applied to stainless steel surfaces (representative of spacecraft surfaces) and two processing methods. data were analyzed by developing a probabilistic model of the experimental process, from stainless steel coupon inoculation through recovery of spores observed in the form of colony forming units. The model quantifies the probability that an individual spore is recovered, a key metric for predicting bioburden and statistically assessing bioburden requirements. A cost function was developed to identify those assay methods that provided optimal bioburden estimation capability. Results show the nylon-flocked swab and the TX3211 wipe yield the highest recovery efficiency of those *** protection at the National Aeronautics and space Administration (NASA) requires bioburden on certain spacecraft to be estimated via sampling in order to comply with biological cleanliness requirements. To achieve this, the recovery efficienc

关键词： planetary protection recovery efficiency assay bioburden

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DAW: exploring the better weighting function for semi-supervised semantic segmentation 23

DAW: exploring the better weighting function for semi-superv...

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Proceedings of the 37th International conference on Neural Information processing Systems

作者： Rui Sun Huayu Mai Tianzhu Zhang Feng Wu Deep Space Exploration Laboratory/School of Information Science and Technology University of Science and Technology of China Deep Space Exploration Laboratory/School of Information Science and Technology University of Science and Technology of China and Institute of Artificial Intelligence Hefei Comprehensive National Science Center

The critical challenge of semi-supervised semantic segmentation lies how to fully exploit a large volume of unlabeled data to improve the model's generalization performance for robust segmentation. Existing methods tend to employ certain criteria (weighting function) to select pixel-level pseudo labels. However, the trade-off exists between inaccurate yet utilized pseudo-labels, and correct yet discarded pseudo-labels in these methods when handling pseudo-labels without thoughtful consideration of the weighting function, hindering the generalization ability of the model. In this paper, we systematically analyze the trade-off in previous methods when dealing with pseudo-labels. We formally define the trade-off between inaccurate yet utilized pseudo-labels, and correct yet discarded pseudolabels by explicitly modeling the confidence distribution of correct and inaccurate pseudo-labels, equipped with a unified weighting function. To this end, we propose Distribution-Aware Weighting (DAW) to strive to minimize the negative equivalence impact raised by the trade-off. We find an interesting fact that the optimal solution for the weighting function is a hard step function, with the jump point located at the intersection of the two confidence distributions. Besides, we devise distribution alignment to mitigate the issue of the discrepancy between the prediction distributions of labeled and unlabeled data. Extensive experimental results on multiple benchmarks including mitochondria segmentation demonstrate that DAW performs favorably against state-of-the-art methods. Code is available at https://***/yuisuen/DAW.

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Inverse-Designed Optical Metagratings for Free-space Integral Equations Solving

Inverse-Designed Optical Metagratings for Free-Space Integra...

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conference on Lasers and Electro-Optics Europe (CLEO EUROPE)

作者： Andrea Cordaro Brian Edwards Vahid Nikkhah Andrea Alù Nader Engheta Albert Polman Institute of Physics University of Amsterdam Amsterdam The Netherlands Center for Nanophotonics NWO-Institute AMOLF Amsterdam The Netherlands Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia USA Photonics Initiative Advanced Science Research Center City University of New York New York USA Physics Program Graduate Center City University of New York New York USA

ISBN: (纸本)9798350345995

The world's ever-growing need for efficient computing has been driving researchers from diverse research fields to explore alternatives to the current digital computing paradigm. In this context, the field of all-optical analog processing is gaining significant attention opening new possibilities to overcome the bottlenecks of standard microelectronics [1–5]. We present a Si-based optical metastructure that solves Fredholm integral equations of the second kind in a fully analog fashion at optical frequencies. We exploit the analogy between the integral equation solving and the behavior of an optimized periodic metagrating coupled to a feedback system. At the foundations of this mapping lies the possibility of designing the S-matrix of a periodic structure by setting its periodicity (i.e., the number of input/output modes and hence the dimension of the S-matrix) and optimizing its unit cell (i.e., optimizing the coupling of light into the defined diffraction modes in amplitude and phase), as shown in Fig. 1a. Next, we show how the designed metastructure effectively solves the problem of interest and compare the metasurface-based solution to the ideal solution. We show that electron beam lithography and reactive ion etching provide the spatial resolution required to create a hardware representation of a predefined Kernel, with relatively small deviations between experiments and simulations. We optically characterize the output for different input signals showing good agreement with the ideal simulated response and use the data to retrieve the solution experimentally provided by the metadevice (see Fig. 1b). Fig. 1 A. Schematic of the proposed structure. A silicon metasurface is patterned on top of a sapphire substrate. The superstrate consists of $\text{SiO}_{2}$ with a semi-transparent au mirror on top. Scale-bar 500 nm b. Estimate of the solution to the integral equation obtained by the fabricated metadevice.

关键词： Crosstalk Electron beam lithography Light diffraction Modes Phase Spatial resolution

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Reinforcement Learning with Temporal-Logic-Based Causal Diagrams 1

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Machine Learning and Knowledge Extraction 7th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain conference, CD-MAKE 2023

作者： Paliwal, Yash Roy, Rajarshi Gaglione, Jean-Raphaël Baharisangari, Nasim Neider, Daniel Duan, Xiaoming Topcu, Ufuk Xu, Zhe Arizona State University TempeAZ United States Max Planck Institute for Software Systems Kaiserslautern Germany University of Texas at Austin AustinTX United States TU Dortmund University Dortmund Germany Center for Trustworthy Data Science and Security University Alliance Ruhr Dortmund Germany Department of Automation Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9783031408373

ISBN: (纸本)9783031408366

We study a class of reinforcement learning (RL) tasks where the objective of the agent is to accomplish temporally extended goals. In this setting, a common approach is to represent the tasks as deterministic finite automata (DFA) and integrate them into the state-space for RL algorithms. However, while these machines model the reward function, they often overlook the causal knowledge about the environment. To address this limitation, we propose the Temporal-Logic-based Causal Diagram (TL-CD) in RL, which captures the temporal causal relationships between different properties of the environment. We exploit the TL-CD to devise an RL algorithm in which an agent requires significantly less exploration of the environment. To this end, based on a TL-CD and a task DFA, we identify configurations where the agent can determine the expected rewards early during an exploration. Through a series of case studies, we demonstrate the benefits of using TL-CDs, particularly the faster convergence of the algorithm to an optimal policy due to reduced exploration of the environment. © 2023, IFIP International Federation for Information processing.

关键词： Reinforcement learning

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Gaia data Release 3: Catalogue validation

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Astronomy and Astrophysics 2023年 674卷

作者： Babusiaux, C. Fabricius, C. Khanna, S. Muraveva, T. Reylé, C. Spoto, F. Vallenari, A. Luri, X. Arenou, F. Álvarez, M.A. Anders, F. Antoja, T. Balbinot, E. Barache, C. Bauchet, N. Bossini, D. Busonero, D. Cantat-Gaudin, T. Carrasco, J.M. Dafonte, C. Diakité, S. Figueras, F. Garcia-Gutierrez, A. Garofalo, A. Helmi, A. Jiménez-Arranz, A. Jordi, C. Kervella, P. Kostrzewa-Rutkowska, Z. Leclerc, N. Licata, E. Manteiga, M. Masip, A. Monguió, M. Ramos, P. Robichon, N. Robin, A.C. Romero-Gómez, M. Sáez, A. Santoveña, R. Spina, L. Torralba Elipe, G. Weiler, M. Univ. Grenoble Alpes CNRS IPAG Grenoble38000 France GEPI Observatoire de Paris Université PSL CNRS 5 Place Jules Janssen Meudon92190 France Martí i Franquès 1 Barcelona08028 Spain Kapteyn Astronomical Institute University of Groningen Landleven 12 Groningen9747 AD Netherlands INAF - Osservatorio di Astrofisica e Scienza dello Spazio di Bologna via Piero Gobetti 93/3 Bologna40129 Italy Institut UTINAM UMR 6213 CNRS University of Bourgogne Franche-Comté OSU THETA 41 bis avenue de l'Observatoire Besançon25000 France Mésocentre de Franche-Comté University of Franche-Comté 16 route de Gray BesançonCedex 25030 France Harvard-Smithsonian Center for Astrophysics 60 Garden St. MS 15 CambridgeMA02138 United States INAF Osservatorio Astronomico di Padova Vicolo Osservatorio Padova35131 Italy CITIC Department of Computer Science and Information Technologies University of A Coruña Campus de Elviña s/n Coruña15071 A Spain SYRTE Observatoire de Paris Université PSL CNRS Sorbonne Université LNE 61 avenue de l'Observatoire Paris75014 France Instituto de Astrofísica e Cióncias do Espaço Universidade do Porto CAUP Rua das Estrelas Porto4150-762 Portugal INAF 'Osservatorio Astrofisico di Torino Via Osservatorio 20 Pino Torinese10025 Italy LESIA Observatoire de Paris Université PSL CNRS Sorbonne Université Université Paris Cité 5 place Jules Janssen Meudon92195 France Leiden Observatory Leiden University Niels Bohrweg 2 Leiden2333 CA Netherlands SRON Netherlands Institute for Space Research Niels Bohrweg 4 Leiden2333 CA Netherlands CITIC Department of Nautical Sciences and Marine Engineering University of A Coruña Campus de Elviña S/N Coruña15071 A Spain Observatoire astronomique de Strasbourg Université de Strasbourg CNRS 11 rue de l'Université Strasbourg67000 France Max-Planck-Institut für Astronomie Königstuhl 17 Heidelberg69117 Germany

Context. The third Gaia data release (DR3) provides a wealth of new data products. The early part of the release, Gaia EDR3, already provided the astrometric and photometric data for nearly two billion sources. The full release now adds improved parameters compared to Gaia DR2 for radial velocities, astrophysical parameters, variability information, light curves, and orbits for Solar System objects. The improvements are in terms of the number of sources, the variety of parameter information, precision, and accuracy. For the first time, Gaia DR3 also provides a sample of spectrophotometry and spectra obtained with the Radial Velocity Spectrometer, binary star solutions, and a characterisation of extragalactic object candidates. Aims. Before the publication of the catalogue, these data have undergone a dedicated transversal validation process. The aim of this paper is to highlight limitations of the data that were found during this process and to provide recommendations for the usage of the catalogue. Methods. The validation was obtained through a statistical analysis of the data, a confirmation of the internal consistency of different products, and a comparison of the values to external data or models. Results. Gaia DR3 is a new major step forward in terms of the number, diversity, precision, and accuracy of the Gaia products. As always in such a large and complex catalogue, however, issues and limitations have also been found. Detailed examples of the scientific quality of the Gaia DR3 release can be found in the accompanying data-processing papers as well as in the performance verification papers. Here we focus only on the caveats that the user should be aware of to scientifically exploit the data. © 2023 EDP Sciences. All rights reserved.

关键词： data handling

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Toward re-identifying any animal 23

Toward re-identifying any animal

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Proceedings of the 37th International conference on Neural Information processing Systems

作者： Bingliang Jiao Lingqiao Liu Liying Gao Ruiqi Wu Guosheng Lin Peng Wang Yanning Zhang School of Computer Science Northwestern Polytechnical University China and Ningbo Institute Northwestern Polytechnical University China and National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean China and Nanyang Technological University Singapore The University of Adelaide Australia School of Computer Science Northwestern Polytechnical University China and Ningbo Institute Northwestern Polytechnical University China and National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean China Nanyang Technological University Singapore

The current state of re-identification (ReID) models poses limitations to their applicability in the open world, as they are primarily designed and trained for specific categories like person or vehicle. In light of the importance of ReID technology for tracking wildlife populations and migration patterns, we propose a new task called "Re-identify Any Animal in the Wild" (ReID-AW). This task aims to develop a ReID model capable of handling any unseen wildlife category it encounters. To address this challenge, we have created a comprehensive dataset called Wildlife-71, which includes ReID data from 71 different wildlife categories. This dataset is the first of its kind to encompass multiple object categories in the realm of ReID. Furthermore, we have developed a universal re-identification model named UniReID specifically for the ReID-Aw task. To enhance the model's adaptability to the target category, we employ a dynamic prompting mechanism using category-specific visual prompts. These prompts are generated based on knowledge gained from a set of pre-given images within the target category. Additionally, we leverage explicit semantic knowledge derived from the large-scale pre-trained language model, GPT-4. This allows UniReID to focus on regions that are particularly useful for distinguishing individuals within the target category. Extensive experiments have demonstrated the remarkable generalization capability of our UniReID model. It showcases promising performance in handling arbitrary wildlife categories, offering significant advancements in the field of ReID for wildlife conservation and research purposes. Our work is available in https://***/JiaoBL1234/wildlife.

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Sub-ns timing for the Pacific Ocean Neutrino Experiment by optical fiber using Gigabit Ethernet 38

Sub-ns timing for the Pacific Ocean Neutrino Experiment by o...

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38th International Cosmic Ray conference, ICRC 2023

作者： Böhmer, Michael Gernhäuser, Roman Ginzkey, Lea Halliday, Rob Spannfellner, Christian Whitehorn, Nathan Agostini, Matteo Bailly, Nicolai Baron, A.J. Bedard, Jeannette Bellenghi, Chiara Böhmer, Michael Bosma, Cassandra Brussow, Dirk Clark, Ken Crudele, Beatrice Danninger, Matthias De Leo, Fabio Deis, Nathan DeYoung, Tyce Dinkel, Martin Garriz, Jeanne Gärtner, Andreas Gernhäuser, Roman Ghuman, Dilraj Gousy-Leblanc, Vincent Grant, Darren Haack, Christian Halliday, Robert Hatch, Patrick Henningsen, Felix Holzapfel, Kilian Jenkyns, Reyna Kerscher, Tobias Kerschtien, Shane Kopański, Konrad Kopper, Claudio Krauss, Carsten B. Kulin, Ian Kurahashi, Naoko Lai, Paul C.W. Lavallee, Tim Leismüller, Klaus Leys, Sally Li, Ruohan Malecki, Pawel McElroy, Thomas Maunder, Adam Trejo, Santiago Miro Miller, Caleb Molberg, Nathan Moore, Roger Niederhausen, Hans Noga, Wojciech Papp, Laszlo Park, Nahee Paulson, Meghan Pirenne, Benoît Qiu, Tom Resconi, Elisa Retza, Niklas Agreda, Sergio Rico Robertson, Steven Ruskey, Albert Schumacher, Lisa Sclafani, Stephen Spannfellner, Christian Stacho, Jakub Taboada, Ignacio Terliuk, Andrii Tradewell, Matt Traxler, Michael Tung, Chun Fai Twagirayezu, Jean Pierre Veenstra, Braeden Wagner, Seann Weaver, Christopher Whitehorn, Nathan Wu, Kinwah Yañez, Juan Pablo Yu, Shiqi Zheng, Yingsong Technische Universität München School of Natural Science James-Franck-Strasse Garching85748 Germany Michigan State University Department of Physics and Astronomy 567 Wilson Rd East LansingMI48824 United States Elmhurst University Department of Physics 190 S Prospect Ave ElmhurstIL60126 United States Ocean Networks Canada University of Victoria VictoriaBC Canada Department of Physics School of Natural Sciences Technical University of Munich Garching Germany Department of Physics Engineering Physics and Astronomy Queen’s University KingstonON Canada Department of Physics Simon Fraser University BurnabyBC Canada Department of Physics University of Alberta EdmontonAB Canada Department of Physics and Astronomy Michigan State University East LansingMI United States Department of Biological Sciences University of Alberta EdmontonAB Canada Gesellschaft für Schwerionenforschung Darmstadt Germany Department of Physics and Astronomy Mullard Space Science Laboratory University College London United Kingdom Department of Physics Drexel University 3141 Chestnut Street PhiladelphiaPA19104 United States School of Physics Center for Relativistic Astrophysics Georgia Institute of Technology AtlantaGA United States Erlangen Centre for Astroparticle Physics Friedrich-Alexander-Universität Erlangen-Nürnberg ErlangenD-91058 Germany H. Niewodniczański Institute of Nuclear Physics Polish Academy of Sciences Radzikowskiego 152 Kraków31-342 Poland

Precise timing inside the Pacific Ocean Neutrino Experiment (P-ONE) will be mandatory to allow synchronization of the DAQ systems inside the P-ONE Optical Modules (P-OMs). The DAQ system is designed to digitize 16 channels of photomultiplier tube (PMT) waveforms at high speed, with a large buffer and waveform pre-processing capabilities. This requires a fast and reliable data path between P-OMs and shore, as well as sub-nanosecond synchronization amongst P-OMs, while keeping the cable design as light-weight as possible to reduce mechanical stress. To meet these requirements, an optical network based on standard Gigabit Ethernet (GbE) on Lattice ECP3/ECP5 FPGAs is presented. It allows syntonous operation of the P-OMs by propagation of a central 125 MHz clock in addition to coarse and fine delay measurements on the point-to-point fiber links, and provides Gigabit Ethernet to all endpoints in the network. This allows precise timing and use of commercial off-the-shelf network components inside the P-OMs and the connected mooring junction box (mJB), serving as a network hub. This greatly simplifies the design process and makes well-tested, easily integrated network standards available for data transport. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Optical fibers

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Hierarchical Geodesic Polynomial Model for Multilevel Analysis of Longitudinal Shape 28th

Hierarchical Geodesic Polynomial Model for Multilevel Analys...

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28th International conference on Information processing in Medical Imaging (IPMI)

作者： Han, Ye Vicory, Jared Gerig, Guido Sabin, Patricia Dewey, Hannah Amin, Silvani Sulentic, Ana Hertz, Christian Jolley, Matthew Paniagua, Beatriz Fishbaugh, James Kitware Inc Clifton Pk NY 12065 USA NYU Tandon Sch Engn Brooklyn NY 11201 USA Childrens Hosp Philadelphia Philadelphia PA 19104 USA

ISBN: (纸本)9783031340475;9783031340482

Longitudinal analysis is a core aspect of many medical applications for understanding the relationship between an anatomical subject's function and its trajectory of shape change over time. Whereas mixed-effects (or hierarchical) modeling is the statistical method of choice for analysis of longitudinal data, we here propose its extension as hierarchical geodesic polynomial model (HGPM) for multilevel analyses of longitudinal shape data. 3D shapes are transformed to a nonEuclidean shape space for regression analysis using geodesics on a high dimensional Riemannian manifold. At the subject-wise level, each individual trajectory of shape change is represented by a univariate geodesic polynomial model on timestamps. At the population level, multivariate polynomial expansion is applied to uni/multivariate geodesic polynomial models for both anchor points and tangent vectors. As such, the trajectory of an individual subject's shape changes over time can be modeled accurately with a reduced number of parameters, and population-level effects from multiple covariates on trajectories can be well captured. The implemented HGPM is validated on synthetic examples of points on a unit 3D sphere. Further tests on clinical 4D right ventricular data show that HGPM is capable of capturing observable effects on shapes attributed to changes in covariates, which are consistent with qualitative clinical evaluations. HGPM demonstrates its effectiveness in modeling shape changes at both subject-wise and population levels, which is promising for future studies of the relationship between shape changes over time and the level of dysfunction severity on anatomical objects associated with disease.

关键词： geodesic regression statistical shape analysis hierarchical modeling longitudinal data

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