Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Daniel Ospina-Acero"'
Publikováno v:
IEEE Transactions on Computational Imaging. 8:41-53
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b70962064e64c2c0d67723b659041104
https://doi.org/10.1109/tci.2021.3137149
https://doi.org/10.1109/tci.2021.3137149
Autor:
Nicolás Montoya-Escobar, Daniel Ospina-Acero, Jorge Andrés Velásquez-Cock, Catalina Gómez-Hoyos, Angélica Serpa Guerra, Piedad Felisinda Gañan Rojo, Lina Maria Vélez Acosta, Juan Pablo Escobar, Natalia Correa-Hincapié, Omar Triana-Chávez, Robin Zuluaga Gallego, Pablo M. Stefani
Publikováno v:
Polymers; Volume 14; Issue 23; Pages: 5199
Cellulose crystallinity can be described according to the crystal size and the crystallinity index (CI). In this research, using Fourier-transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) methods, we studied the crystallinity of three
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4931e91874b63224df5cfe3750c735ba
Publikováno v:
IEEE Transactions on Instrumentation and Measurement. 70:1-10
Electrical capacitance tomography is a widely used sensor modality for flow imaging in many industrial settings. Adaptive electrical capacitance volume tomography (AECVT) extends the capabilities of traditional ECT by enabling direct volumetric imagi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::937d642e477770432e3be68a9cd8d31d
https://doi.org/10.1109/tim.2020.3047482
https://doi.org/10.1109/tim.2020.3047482
Publikováno v:
IEEE Sensors Journal. 20:4925-4939
We present a Relevance Vector Machine (RVM) based algorithm for electrical capacitance tomography (ECT) applications that can concurrently provide image reconstruction results and uncertainty estimates about the reconstruction. To illustrate the RVM
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::442a3eeac456f0a5d2ac359389fdd4ce
https://doi.org/10.1109/jsen.2020.2966990
https://doi.org/10.1109/jsen.2020.2966990
Autor:
Daniel Ospina Acero, Christopher E. Zuccarelli, Zeeshan Zeeshan, Qussai Marashdeh, Fernando L. Teixeira
Publikováno v:
IEEE Transactions on Instrumentation and Measurement. 68:462-473
Electrical capacitance tomography (ECT) exhibits several attractive features that are important for industrial process tomography applications. These features include low cost, high speed, and nonintrusive nature. However, due to its soft-field chara
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::01fc5c620dc447de8dda2c9fa7359d5c
https://doi.org/10.1109/tim.2018.2847918
https://doi.org/10.1109/tim.2018.2847918
Publikováno v:
2020 IEEE SENSORS.
Relevance Vector Machine (RVM) is a machine learning technique relying on Bayesian inference that can be used to solve tomography image reconstruction problems under a probabilistic framework. By highlighting discrepancies between entropy estimates a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::48818cc597534a29fbfe5d9b3249fa8e
https://doi.org/10.1109/sensors47125.2020.9278898
https://doi.org/10.1109/sensors47125.2020.9278898
Publikováno v:
IEEE Sensors Journal. 18:9649-9659
Electrical capacitance tomography (ECT) is a non-invasive and non-intrusive imaging modality that utilizes mutual capacitance measurements between electrode plates to reconstruct the cross-sectional spatial electrical permittivity distribution inside
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c20a8d8abd64649ead43a7132fc7f775
https://doi.org/10.1109/jsen.2018.2871679
https://doi.org/10.1109/jsen.2018.2871679
Publikováno v:
2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting.
We exploit the sparsity inherited from traditional Relevance Vector Machine (RVM) method to efficiently perform the exhaustive search involved in Adaptive RVM operation applied to reconfigurable soft-field tomography sensors. To illustrate these idea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de990f411c68c09b512bda9354da1e00
https://doi.org/10.1109/apusncursinrsm.2019.8889129
https://doi.org/10.1109/apusncursinrsm.2019.8889129
Publikováno v:
2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting.
We describe a deep convolutional neural network (CNN) approach for nonlinear electromagnetic (EM) inverse scattering problems. We evaluate the performance of the proposed CNN as a function of the number of layers using different metrics such as struc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cdedc2b767bc2f54c74efe404cf5e792
https://doi.org/10.1109/apusncursinrsm.2019.8888813
https://doi.org/10.1109/apusncursinrsm.2019.8888813
Publikováno v:
2019 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM).
Process tomography is a well established imaging modality to monitor a variety of flow processes in industrial applications. Traditionally, this has been done through imaging of a cross section of the domain. In recent years, much interest has been d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::66415b29cf2ae944c8c134a3ba4abb07
https://doi.org/10.23919/usnc-ursi-nrsm.2019.8713155
https://doi.org/10.23919/usnc-ursi-nrsm.2019.8713155