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IEEE International Conference on Image Processing

作者： Javier Mateos Antonio Lopez Miguel Vega Rafael Molina Aggelos K. Katsaggelos Dpt. de Ciencias de la Computacion e I. A. Univ. de Granada Dpt. de Lenguajes y Sistemas Informaticos Univ. de Granada Dpt. of Electrical Engineering and Computer Science Northwestern University

ISBN: (纸本)9781467399623

Passive Millimeter Wave Images currently used to detect hidden threats suffer from low resolution, blur, and a very low signal-to-noise-ratio. These shortcomings render threat detection, both visual and automatic, very challenging. Furthermore, due to the presence of very severe noise, most of the blind image restoration methods fail to recover the system blurring kernel from a single image. In this paper we propose a robust Bayesian multiframe blind image deconvolution method that approximates the posterior distribution of the blur by a Dirichlet distribution. We show that this approach naturally incorporates the non-negativity and normalization constraints for the blur and cope well with the image noise. The performance of the proposed method is tested on both synthetic and real images.

关键词： Passive millimeter wave imaging Blind image deconvolution Variational Dirichlet images deconvolution millimetre wave imaging Seeds blind deconvolution waves waveforms Posterior distribution image noise Blind multiframe

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X-Ray fluorescence image super-resolution using dictionary learning

X-Ray fluorescence image super-resolution using dictionary l...

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IEEE IVMSP Workshop

作者： Qiqin Dai Emeline Pouyet Oliver Cossairt Marc Walton Francesca Casadio Aggelos Katsaggelos Dpt. of Electrical Engineering and Computer Science Northwestern University Center for Scientific Studies in the Arts (NU-ACCESS) Northwestern University

ISBN: (纸本)9781509019304

X-Ray fluorescence (XRF) scanning of works of art is becoming an increasingly popular non-destructive analytical method. The high quality XRF spectra is necessary to obtain significant information on both major and minor elements used for characterization and provenance analysis. However, there is a trade-off between the spatial resolution of an XRF scan and the Signal-to-Noise Ratio (SNR) of each pixel's spectrum, due to the limited scanning time. In this paper, we propose an XRF image super-resolution method to address this trade-off, thus obtaining a high spatial resolution XRF scan with high SNR. We use a sparse representation of each pixel using a dictionary trained from the spectrum samples of the image, while imposing a spatial smoothness constraint on the sparse coefficients. We then increase the spatial resolution of the sparse coefficient map using a conventional super-resolution method. Finally the high spatial resolution XRF image is reconstructed by the high spatial resolution sparse coefficient map and the trained spectrum dictionary.

关键词： Dictionaries Spatial resolution Image reconstruction Mathematical model Signal resolution Signal to noise ratio

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Thematic labeling of Twitter accounts using DBpedia properties

Thematic labeling of Twitter accounts using DBpedia properti...

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International Workshop on Semantic Media Adaptation and Personalization (SMAP)

作者： Gerasimos Razis Ioannis Anagnostopoulos Petr Saloun Computer Science and Biomedical Informatics Dpt. University of Thessaly Lamia Greece Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Czech Republic

ISBN: (纸本)9781509052479

In this paper, we propose an iterative algorithm towards the automatic labeling of Twitter accounts in respect to thematic categories derived from DBpedia properties. We describe the rationale behind the selection of these thematic categories, and discuss their evaluation assessment. Finally, we propose and analyze two generic and adaptable methodologies for discovering the necessary linked data resources for further enhancing the thematic description of Twitter accounts.

关键词： Twitter Labeling Measurement Classification algorithms Tagging Semantics Algorithm design and analysis

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AUTOMATIC PIGMENT IDENTIFICATION ON ROMAN EGYPTIAN PAINTINGS BY USING SPARSE MODELING OF HYPERSPECTRAL IMAGES

AUTOMATIC PIGMENT IDENTIFICATION ON ROMAN EGYPTIAN PAINTINGS...

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European Signal Processing Conference

作者： Neda Rohani Johanna Salvant Sara Bahaadini Oliver Cossairt Marc Walton Aggelos Katsaggelos Dpt. of Electrical Engineering and Computer Science. Northwestern University Center for Scientific Studies in the Arts (NU-ACCESS) Northwestern University

ISBN: (纸本)9781509018918

In this paper, we study the problem of automatic identification of pigments applied to paintings using hyperspectral reflectance data. Here, we cast the problem of pigment identification in a novel way by decomposing the spectrum into pure pigments. The pure pigment exemplars, chosen and prepared in our laboratory based on historic sources and archaeological examples, closely resemble the materials used to make ancient paintings. To validate our algorithm, we created a set of mock-up paintings in our laboratory consisting of a broad palette of mixtures of pure pigments. Our results clearly demonstrate more accurate estimation of pigment composition than purely distance-based methods such as spectral angle mapping (SAM) and spectral correlation mapping (SCM). In addition, we studied hyperspectral imagery acquired of a Roman-Egyptian portrait, excavated from the site of Tebtunis in the Fayum region of Egypt, and dated to about the 2nd century CE. Using ground truth information obtained using Raman spectroscopy, we show qualitatively that our method accurately detects pigment composition for the specific pigments hematite and indigo.

关键词： Pigments Dictionaries Painting Libraries Hyperspectral imaging Image color analysis Signal processing algorithms painting Pigment image colour analysis Signal processing algorithms Dictionaries as Topic hyperspectral imagery Libraries

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Model for the organization, storage and processing of large data banks of physiological variables

Model for the organization, storage and processing of large ...

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International Conference on computers Communications and Control (ICCCC)

作者： Fredi E. Palominos Hernán Diaz Felisa M. Córdova A. Lucio Canete Claudia A. Durán Dpt. Mathematics and Computer Science University of Santiago de Chile Santiago Chile Dpt. Chemistry and Biology University of Santiago de Chile Santiago Chile School of Industrial Engineering University Finis Terrae Santiago Chile Universidad de Santiago de Chile Santiago de Chile CL Dpt. of Industrial Engineering University of Santiago de Chile Santiago Chile

ISBN: (纸本)9781509017362

The proliferation and popularization of new instruments for measuring different types of electrophysiological variables, has generated the need to store huge volumes of information, corresponding to the records obtained by applying this instruments on experimental subjects. Together with this must be added the data derived from the analysis and purification processes. Moreover, several stages involved in the processing of data, is associated with one or more specific methods related to the area of research and to the treatment at which the base information (RAW) is subjected. As a result of this and with the passage of time, various problems occur, which are the most obvious consequence of that data and metadata derived from the treatment processes and analysis, and can end up accumulating and requiring more storage space than the base data. In addition, the enormous amount of information, as it increases over time, can lead to the loss of the link between the processed data, the methods of treatment used, and the analysis performed, so that eventually all becomes simply a huge repository of biometric data, devoid of meaning and sense. Current approaches around the concept of big data, while take over the storage and other aspects such as information search mechanisms, are far from incorporating metadata about the neurophysiological and emotional records. This type of information requires the construction of chronologies of events, including the methods of processing and analysis. In addition, it is required to maintain an adequate link between those responsible for the data (those who recorded and analyzed) and subjects that are under investigation, without breaking confidentiality to which they are entitled. This paper presents an approach founded in a data model that can adequately handle different types of chronologies of physiological and emotional information, ensuring confidentiality of information according to the experimental protocols and relevant ethical

关键词： Electroencephalography Big data Instruments Metadata computers Cleaning

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Horizons: Nuclear Astrophysics in the 2020s and Beyond

arXiv

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arXiv 2022年

作者： Schatz, Hendrik Becerril Reyes, A.D. Best, A. Brown, E.F. Chatziioannou, K. Chipps, K.A. Deibel, C.M. Ezzeddine, R. Galloway, D.K. Hansen, C.J. Herwig, F. Ji, A.P. Lugaro, M. Meisel, Z. Norman, D. Read, J.S. Roberts, L.F. Spyrou, A. Tews, I. Timmes, F.X. Travaglio, C. Vassh, N. Abia, C. Adsley, P. Agarwal, S. Aliotta, M. Aoki, W. Arcones, A. Aryan, A. Bandyopadhyay, A. Banu, A. Bardayan, D.W. Barnes, J. Bauswein, A. Beers, T.C. Bishop, J. Boztepe, T. Côté, B. Caplan, M.E. Champagne, A.E. Clark, J.A. Couder, M. Couture, A. de Mink, S.E. Debnath, S. deBoer, R.J. den Hartogh, J. Denissenkov, P. Dexheimer, V. Dillmann, I. Escher, J.E. Famiano, M.A. Farmer, R. Fisher, R. Fröhlich, C. Frebel, A. Fryer, C. Fuller, G. Ganguly, A.K. Ghosh, S. Gibson, B.K. Gorda, T. Gourgouliatos, K.N. Graber, V. Gupta, M. Haxton, W. Heger, A. Hix, W.R. Ho, W.C.G. Holmbeck, E.M. Hood, A.A. Huth, S. Imbriani, G. Izzard, R.G. Jain, R. Jayatissa, H. Johnston, Z. Kajino, T. Kankainen, A. Kiss, G.G. Kwiatkowski, A. La Cognata, M. Laird, A.M. Lamia, L. Landry, P. Laplace, E. Launey, K.D. Leahy, D. Leckenby, G. Lennarz, A. Longfellow, B. Lovell, A.E. Lynch, W.G. Lyons, S.M. Maeda, K. Masha, E. Matei, C. Merc, J. Messer, B. Montes, F. Mukherjee, A. Mumpower, M. Neto, D. Nevins, B. Newton, W.G. Nguyen, L.Q. Nishikawa, K. Nishimura, N. Nunes, F.M. O’Connor, E. O’Shea, B.W. Ong, W.-J. Pain, S.D. Pajkos, M.A. Pignatari, M. Pizzone, R.G. Placco, V.M. Plewa, T. Pritychenko, B. Psaltis, A. Puentes, D. Qian, Y.-Z. Radice, D. Rapagnani, D. Rebeiro, B.M. Reifarth, R. Richard, A.L. Rijal, N. Roederer, I.U. Rojo, J.S. Sk, J. Saito, Y. Schwenk, A. Sergi, M.L. Sidhu, R.S. Simon, A. Sivarani, T. Skúladóttir, Á. Smith, M.S. Spiridon, A. Sprouse, T.M. Starrfield, S. Steiner, A.W. Strieder, F. Sultana, I. Surman, R. Szücs, T. Tawfik, A. Thielemann, F. Trache, L. Trappitsch, R. Department of Physics and Astronomy Michigan State University East LansingMI48824 United States Facility for Rare Isotope Beams Michigan State University East LansingMI48824 United States United States Department of Physics University of Naples"Federico II" Napoli80126 Italy INFN - Sezione di Napoli Napoli80126 Italy Department of Computational Mathematics Science and Engineering MichiganState University East LansingMI48824 United States Department of Physics California Institute of Technology PasadenaCA91125 United States LIGO Laboratory California Institute of Technology PasadenaCA91125 United States Physics Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Physics and Astronomy University of Tennessee Knoxville KnoxvilleTN37996 United States Department of Physics and Astronomy Louisiana State University Baton RougeLA70803 United States Department of Astronomy University of Florida GainesvilleFL32601 United States School of Physics and Astronomy Monash University VIC3800 Australia OzGRav-Monash School of Physics & Astronomy Monash University VIC3800 Australia Goethe University Frankfurt Institute for Applied Physics Max-von-Laue-Str. 12 Frankfurt am Main60438 Germany Technical University of Darmstadt Institute for Nuclear Physics Germany Max Planck Institute for Astronomy Heidelberg Germany Department of Physics and Astronomy University of Victoria VictoriaBCV8P 5C2 Canada Department of Astronomy & Astrophysics University of Chicago 5640 S Ellis Avenue ChicagoIL60637 United States Kavli Institute for Cosmological Physics University of Chicago ChicagoIL60637 United States Excellence Centre of the Hungarian Academy of Sciences Konkoly-Thege Miklós út 15-17 BudapestH-1121 Hungary ELTE Eötvös Loránd University Institute of Physics Pázmány Péter sétány 1/A Budapest1117 Hungary Institute of Nuclear & Particle Physics Department of Physics & Astronomy Ohio University AthensOH45701

Nuclear Astrophysics is a field at the intersection of nuclear physics and astrophysics, which seeks to understand the nuclear engines of astronomical objects and the origin of the chemical elements. This white paper summarizes progress and status of the field, the new open questions that have emerged, and the tremendous scientific opportunities that have opened up with major advances in capabilities across an ever growing number of disciplines and subfields that need to be integrated. We take a holistic view of the field discussing the unique challenges and opportunities in nuclear astrophysics in regards to science, diversity, education, and the interdisciplinarity and breadth of the field. Clearly nuclear astrophysics is a dynamic field with a bright future that is entering a new era of discovery opportunities. © 2022, CC BY-NC-SA.

关键词： Astrophysics

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Reducing the size of the optimization problems in fuzzy ontology reasoning 11

Reducing the size of the optimization problems in fuzzy onto...

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11th International Workshop on Uncertainty Reasoning for the Semantic Web, URSW 2015 - collocated with the 14th International Semantic Web Conference, ISWC 2015

作者： Bobillo, Fernando Straccia, Umberto Dpt. of Computer Science and Systems Engineering University of Zaragoza Spain Pisa Italy

Fuzzy ontologies allow the representation of imprecise structured knowledge, typical in many real-world application domains. A key factor in the practical success of fuzzy ontologies is the availability of highly optimized reasoners. This short paper discusses a novel optimization technique: a reduction of the size of the optimization problems obtained during the inference by the fuzzy ontology reasoner fuzzyDL.

关键词： Ontology

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BAYESIAN LOGISTIC REGRESSION WITH SPARSE GENERAL REPRESENTATION PRIOR FOR MULTISPECTRAL IMAGE CLASSIFICATION

BAYESIAN LOGISTIC REGRESSION WITH SPARSE GENERAL REPRESENTAT...

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IEEE International Conference on Image Processing

作者： Juan G. Serra Pablo Ruiz Rafael Molina Aggelos K. Katsaggelos Dpto. de Ciencia de la Computacion e I.A. Universidad de Granada Dpt. of Electrical Engineering and Computer Science Northwestern University

ISBN: (纸本)9781467399623

In this work we address the multispectral image classification problem from a Bayesian perspective. We develop an algorithm which utilizes the logistic regression function as the observation model in a probabilistic framework, Super-Gaussian (SG) priors which promote sparsity on the adaptive coefficients, and Variational inference to obtain estimates of all the model unknowns. The proposed algorithm is validated on both synthetic and real experiments and compared with other state-of-the-art methods, such as Support Vector Machine and Gaussian Processes, demonstrating its improved performance.

关键词： Image Classification Bayes Methods Inference Algorithms Image classification Bayes methods Inference algorithms Variational Inference MULTISPECTRAL Taxonomy Gaussian processes regression function images Support Vector Network

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Maximin Fairness-profit Tradeoff in Project Budget Allocation

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Procedia computer science 2016年 100卷 313-320页

作者： Maurizio Naldi Gaia Nicosia Andrea Pacifici Ulrich Pferschy Dpt. of Computer Science and Civil Engineering University of Rome Tor Vergata Rome Italy Dipartimento di Ingegneria Universita’ Roma Tre Rome Italy Department of Statistics and Operations Research University of Graz Graz Austria

Companies typically select those projects that maximize their profit as the primary criterion, within the limited budget at their disposal. This criterion may lead to some company departments getting an exceedingly large share of the overall budget and induce a negative perception of unfairness among the less favourite ones. We investigate how profit optimization can be sought after while achieving the desired level of fairness at the same time. Adopting a maximin approach to fairness and using an Integer Linear Programming solver, we show that a linear trade-off is possible, since fairness and profit exhibit a nearly perfect linear anticorrelation. Fairness can be improved by even a relatively small reduction of profit, especially in large companies (i.e., managing a large number of projects).

关键词： Budget allocation Multi-project management Project Portfolio Fairness

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Variational Gaussian process for missing label crowdsourcing classification problems

Variational Gaussian process for missing label crowdsourcing...

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IEEE Workshop on Machine Learning for Signal Processing

作者： Pablo Ruiz Emre Besler Rafael Molina Aggelos K. Katsaggelos Dpto. de Ciencias de la Computación e I.A. Universidad de Granada Dpt. of Electrical Engineering and Computer Science Northwestern University

ISBN: (纸本)9781509007479

In this paper we address the crowdsourcing problem, where a classifier must be trained without knowing the real labels. For each sample, labels (which may not be the same) are provided by different annotators (usually with different degrees of expertise). The problem is formulated using Bayesian modeling, and considers scenarios where each annotator may label a subset of the training set samples only. Although Bayesian approaches have been previously proposed in the literature, we introduce Variational Bayes inference to develop an iterative algorithm where all latent variables are automatically estimated. In the experimental section the proposed model is evaluated and compared with other state-of-the-art methods on two real datasets.

关键词： Crowdsourcing Bayes methods Reliability Probabilistic logic Training Gaussian processes Noise measurement

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