Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Antoine Fagette"'
Autor:
Yassine Habib, Panagiotis Papadakis, Cédric Le Barz, Antoine Fagette, Tiago Gonçalves, Cédric Buche
Publikováno v:
2023 9th International Conference on Automation, Robotics and Applications (ICARA).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5860fe3f0600cae3d4fc59224374b850
https://doi.org/10.1109/icara56516.2023.10125712
https://doi.org/10.1109/icara56516.2023.10125712
Publikováno v:
2022 IEEE Symposium Series on Computational Intelligence (SSCI).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d2f6864af57ba50d8b35a40d569dfa09
https://doi.org/10.1109/ssci51031.2022.10022206
https://doi.org/10.1109/ssci51031.2022.10022206
Publikováno v:
FUSION
This paper presents a study on electromagnetic emitter localization using time difference of arrival (TDOA) and frequency-difference-of-arrival (FDOA) measurements acquired by moving sensors in the presence of communication constraints. The problem i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5279c1fc274ac0938cc297c252dbc7f8
https://doi.org/10.23919/fusion45008.2020.9190509
https://doi.org/10.23919/fusion45008.2020.9190509
Publikováno v:
ITSC
Besides outliers generated from the data collection stage, anomalies in traffic data can also be valid data characterizing unusual traffic activities. Detecting these anomalies in spatiotemporal traffic activities can provide practical insights for t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e182d47cdf61ffaab53f3ab13ce28dad
https://doi.org/10.1109/itsc.2019.8917169
https://doi.org/10.1109/itsc.2019.8917169
Publikováno v:
2017 Winter Simulation Conference (WSC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bd691beb854c8ad82463a044bc6f9698
https://doi.org/10.1109/wsc.2017.8247864
https://doi.org/10.1109/wsc.2017.8247864
Publikováno v:
OCEANS 2017 - Aberdeen.
In this article we are addressing the problem of automatic detection and classification of underwater mines on images generated by a Synthetic Aperture Sonar (SAS). To tackle this problem, we are investigating the use of Machine Learning techniques,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3692bb45cd92e150ee1a08b7378b2ba3
https://doi.org/10.1109/oceanse.2017.8084910
https://doi.org/10.1109/oceanse.2017.8084910
Publikováno v:
2016 IEEE Region 10 Conference (TENCON).
Due to the non-predictive nature of disasters, there is little first-hand data available which in turn is a serious constraint to conduct research on the implication of disasters on urban population. Computational sociology aims at by-passing this is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fc2ce60e212c308137f65d8872443c4e
https://doi.org/10.1109/tencon.2016.7847965
https://doi.org/10.1109/tencon.2016.7847965
Autor:
Sidney Tio, Antoine Fagette, Stephen Kheh Chew Chai, Mohd. Faisal Bin Zainal Abiden, Shawn Thian, Serge Landry, Hui Min Ng
Publikováno v:
Complex Systems Design & Management Asia ISBN: 9783319296425
CSDM Asia
CSDM Asia
In this paper we discuss how findings from social sciences research can be injected into a complex urban environment simulator in order to increase the level of realism of the simulated behaviors with respect to the local context. Our team, composed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::02ecc212adfb665629f90b4f4681f2c2
https://doi.org/10.1007/978-3-319-29643-2_18
https://doi.org/10.1007/978-3-319-29643-2_18
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319255293
ICPRAM (Selected Papers)
ICPRAM (Selected Papers)
This paper deal with the flow tracking topic applied to dense crowds of pedestrians. Using the estimated density, a cloud of particles is spread on the image and propagated according to the optical flow. Each particles embedding physical properties s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5e2ff60860266bab97da8f909b2b7242
https://doi.org/10.1007/978-3-319-25530-9_16
https://doi.org/10.1007/978-3-319-25530-9_16
Publikováno v:
Pattern Recognition Letters
Pattern Recognition Letters, Elsevier, 2013, pp.1-27
Pattern Recognition Letters, 2013, pp.1-27
Pattern Recognition Letters, Elsevier, 2013, pp.1-27
Pattern Recognition Letters, 2013, pp.1-27
We propose a fully unsupervised method for the detection of dense crowds in images.We build multiscale texture-based feature vectors over the image.We use the diffusion maps algorithm to perform the clustering of our data.We propose the use of a quad
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a6aadc5afeeb352313d454077dd99d38
https://hal.archives-ouvertes.fr/hal-00904210
https://hal.archives-ouvertes.fr/hal-00904210