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Carlos Arteta

Showing results (1-10 of 11) with videos related to

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Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|January 5, 2013
Learning to detect cells using non-overlapping extremal regionsCarlos Arteta, Victor Lempitsky, J Alison Noble, et al.
Medical Image Analysis|May 19, 2015
Detecting overlapping instances in microscopy images using extremal region treesCarlos Arteta, Victor Lempitsky, J Alison Noble, et al.
Science Advances|April 18, 2018
Crystal nucleation in metallic alloys using x-ray radiography and machine learningEnzo Liotti, Carlos Arteta, Andrew Zisserman, et al.
Scientific Data|March 29, 2020
Processing citizen science- and machine-annotated time-lapse imagery for biologically meaningful metricsFiona M Jones, Carlos Arteta, Andrew Zisserman, et al.
Physiological Measurement|October 30, 2019
Cardio-respiratory signal extraction from video camera data for continuous non-contact vital sign monitoring using deep learningSitthichok Chaichulee, Mauricio Villarroel, João Jorge, et al.
NPJ Digital Medicine|December 25, 2019
Non-contact physiological monitoring of preterm infants in the Neonatal Intensive Care UnitMauricio Villarroel, Sitthichok Chaichulee, João Jorge, et al.
Scientific Data|September 8, 2019
Author Correction: Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch projectFiona M Jones, Campbell Allen, Carlos Arteta, et al.
Scientific Data|June 27, 2018
Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch projectFiona M Jones, Campbell Allen, Carlos Arteta, et al.
Thorax|March 7, 2020
External validation of a convolutional neural network artificial intelligence tool to predict malignancy in pulmonary nodulesDavid R Baldwin, Jennifer Gustafson, Lyndsey Pickup, et al.
American Journal of Respiratory and Critical Care Medicine|April 25, 2020
Assessing the Accuracy of a Deep Learning Method to Risk Stratify Indeterminate Pulmonary NodulesPierre P Massion, Sanja Antic, Sarim Ather, et al.
Pageof 2

Showing results (1-10 of 11) with videos related to

Sort By:
Pageof 2
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|January 5, 2013
Learning to detect cells using non-overlapping extremal regionsCarlos Arteta, Victor Lempitsky, J Alison Noble, et al.
Medical Image Analysis|May 19, 2015
Detecting overlapping instances in microscopy images using extremal region treesCarlos Arteta, Victor Lempitsky, J Alison Noble, et al.
Science Advances|April 18, 2018
Crystal nucleation in metallic alloys using x-ray radiography and machine learningEnzo Liotti, Carlos Arteta, Andrew Zisserman, et al.
Scientific Data|March 29, 2020
Processing citizen science- and machine-annotated time-lapse imagery for biologically meaningful metricsFiona M Jones, Carlos Arteta, Andrew Zisserman, et al.
Physiological Measurement|October 30, 2019
Cardio-respiratory signal extraction from video camera data for continuous non-contact vital sign monitoring using deep learningSitthichok Chaichulee, Mauricio Villarroel, João Jorge, et al.
NPJ Digital Medicine|December 25, 2019
Non-contact physiological monitoring of preterm infants in the Neonatal Intensive Care UnitMauricio Villarroel, Sitthichok Chaichulee, João Jorge, et al.
Scientific Data|September 8, 2019
Author Correction: Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch projectFiona M Jones, Campbell Allen, Carlos Arteta, et al.
Scientific Data|June 27, 2018
Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch projectFiona M Jones, Campbell Allen, Carlos Arteta, et al.
Thorax|March 7, 2020
External validation of a convolutional neural network artificial intelligence tool to predict malignancy in pulmonary nodulesDavid R Baldwin, Jennifer Gustafson, Lyndsey Pickup, et al.
American Journal of Respiratory and Critical Care Medicine|April 25, 2020
Assessing the Accuracy of a Deep Learning Method to Risk Stratify Indeterminate Pulmonary NodulesPierre P Massion, Sanja Antic, Sarim Ather, et al.
Pageof 2