| 1. |
- Tabiri, S, et al.
(author)
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- 2021
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swepub:Mat__t
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| 2. |
- Bravo, L, et al.
(author)
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- 2021
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swepub:Mat__t
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| 3. |
- Glasbey, JC, et al.
(author)
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- 2021
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swepub:Mat__t
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| 4. |
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| 5. |
- Barausse, Enrico, et al.
(author)
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Prospects for fundamental physics with LISA
- 2020
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In: General Relativity and Gravitation. - : SPRINGER/PLENUM PUBLISHERS. - 0001-7701 .- 1572-9532. ; 52:8
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Journal article (other academic/artistic)abstract
- In this paper, which is of programmatic rather than quantitative nature, we aim to further delineate and sharpen the future potential of the LISA mission in the area of fundamental physics. Given the very broad range of topics that might be relevant to LISA,we present here a sample of what we view as particularly promising fundamental physics directions. We organize these directions through a "science-first" approach that allows us to classify how LISA data can inform theoretical physics in a variety of areas. For each of these theoretical physics classes, we identify the sources that are currently expected to provide the principal contribution to our knowledge, and the areas that need further development. The classification presented here should not be thought of as cast in stone, but rather as a fluid framework that is amenable to change with the flow of new insights in theoretical physics.
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| 6. |
- Kristan, M., et al.
(author)
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The Eighth Visual Object Tracking VOT2020 Challenge Results
- 2020
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In: Computer Vision. - Cham : Springer International Publishing. - 9783030682378 ; , s. 547-601
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Conference paper (peer-reviewed)abstract
- The Visual Object Tracking challenge VOT2020 is the eighth annual tracker benchmarking activity organized by the VOT initiative. Results of 58 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The VOT2020 challenge was composed of five sub-challenges focusing on different tracking domains: (i) VOT-ST2020 challenge focused on short-term tracking in RGB, (ii) VOT-RT2020 challenge focused on “real-time” short-term tracking in RGB, (iii) VOT-LT2020 focused on long-term tracking namely coping with target disappearance and reappearance, (iv) VOT-RGBT2020 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2020 challenge focused on long-term tracking in RGB and depth imagery. Only the VOT-ST2020 datasets were refreshed. A significant novelty is introduction of a new VOT short-term tracking evaluation methodology, and introduction of segmentation ground truth in the VOT-ST2020 challenge – bounding boxes will no longer be used in the VOT-ST challenges. A new VOT Python toolkit that implements all these novelites was introduced. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website (http://votchallenge.net ).
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| 7. |
- Richard, G., et al.
(author)
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Multi Modal Verification for Teleservices and Security Applications (M2VTS)
- 1999
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In: IEEE International Conference on Multimedia Computing and Systems. - Los Alamitos : IEEE. - 0769502539 ; , s. 1061-1064
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Conference paper (other academic/artistic)abstract
- This paper presents the European ACTS project M2VTS which stands for Multi Modal Verification for Teleservices and Security Applications. The primary goal of this project is to address the issue of secured access to local and centralised services in a multimedia environment. The main objective is to extend the scope of application of network-based services by adding novel and intelligent functionalities, enabled by automatic verification systems combining multimodal strategies (secured access based on speech, image or other information). The objectives of the project are also to show that limitations of individual technologies (speaker verification, frontal face authentication, profile identification,...) can be overcome by relying on multi-modal decisions (combination or fusion of these technologies).
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| 8. |
- Matas, J., et al.
(author)
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Comparison of face verification results on the XM2VTS database
- 2000
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In: Proceedings of the 15th International Conference on Pattern Recognition (ICPR'00) - Volume 4. - 0769507506 ; , s. 858-863
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Conference paper (other academic/artistic)abstract
- The paper presents results of the face verification contest that was organized in conjunction with International Conference on Pattern Recognition 2000 [14]. Participants had to use identical data sets from a large, publicly available multimodal database XM2VTSDB. Training and evaluation was carried out according to an a priori known protocol ([7]). Verification results of all tested algorithms have been collected and made public on the XM2VTSDB website [15], facilitating large scale experiments on classifier combination and fusion. Tested methods included, among others, representatives of the most common approaches to face verification - elastic graph matching, Fisher's linear discriminant and Support vector machines.
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| 9. |
- Cescutti, G., et al.
(author)
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MINCE I. Presentation of the project and of the first year sample
- 2022
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In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 668
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Journal article (peer-reviewed)abstract
- Context. In recent years, Galactic archaeology has become a particularly vibrant field of astronomy, with its main focus set on the oldest stars of our Galaxy. In most cases, these stars have been identified as the most metal-poor. However, the struggle to find these ancient fossils has produced an important bias in the observations - in particular, the intermediate metal-poor stars (-2.5 < [Fe/H] < -1.5) have been frequently overlooked. The missing information has consequences for the precise study of the chemical enrichment of our Galaxy, in particular for what concerns neutron capture elements and it will be only partially covered by future multi object spectroscopic surveys such as WEAVE and 4MOST.Aims. Measuring at Intermediate Metallicity Neutron Capture Elements (MINCE) is gathering the first high-quality spectra (high signal-to-noise ratio, S/N, and high resolution) for several hundreds of bright and metal-poor stars, mainly located in our Galactic halo.Methods. We compiled our selection mainly on the basis of Gaia data and determined the stellar atmospheres of our sample and the chemical abundances of each star.Results. In this paper, we present the first sample of 59 spectra of 46 stars. We measured the radial velocities and computed the Galactic orbits for all stars. We found that 8 stars belong to the thin disc, 15 to disrupted satellites, and the remaining cannot be associated to the mentioned structures, and we call them halo stars. For 33 of these stars, we provide abundances for the elements up to zinc. We also show the chemical evolution results for eleven chemical elements, based on recent models.Conclusions. Our observational strategy of using multiple telescopes and spectrographs to acquire high S/N and high-resolution spectra for intermediate-metallicity stars has proven to be very efficient, since the present sample was acquired over only about one year of observations. Finally, our target selection strategy, after an initial adjustment, proved satisfactory for our purposes.
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| 10. |
- Kristan, Matej, et al.
(author)
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The Visual Object Tracking VOT2016 Challenge Results
- 2016
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In: COMPUTER VISION - ECCV 2016 WORKSHOPS, PT II. - Cham : SPRINGER INT PUBLISHING AG. - 9783319488813 - 9783319488806 ; , s. 777-823
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Conference paper (peer-reviewed)abstract
- The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers are presented, with a large number of trackers being published at major computer vision conferences and journals in the recent years. The number of tested state-of-the-art trackers makes the VOT 2016 the largest and most challenging benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the Appendix. The VOT2016 goes beyond its predecessors by (i) introducing a new semi-automatic ground truth bounding box annotation methodology and (ii) extending the evaluation system with the no-reset experiment.
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