Search Results for author: Gerardo Flores

Found 8 papers, 2 papers with code

Transition control of a tail-sitter UAV using recurrent neural networks

no code implementations29 Jun 2020 Alejandro Flores, Gerardo Flores

This paper presents the implementation of a Recurrent Neural Network (RNN) based-controller for the stabilization of the flight transition maneuver (hover-cruise and vice versa) of a tail-sitter UAV.

Desmoking laparoscopy surgery images using an image-to-image translation guided by an embedded dark channel

1 code implementation19 Apr 2020 Sebastián Salazar-Colores, Hugo Alberto-Moreno, César Javier Ortiz-Echeverri, Gerardo Flores

In laparoscopic surgery, the visibility in the image can be severely degraded by the smoke caused by the $CO_2$ injection, and dissection tools, thus reducing the visibility of organs and tissues.

Generative Adversarial Network Image-to-Image Translation +2

Modelling EHR timeseries by restricting feature interaction

no code implementations14 Nov 2019 Kun Zhang, Yuan Xue, Gerardo Flores, Alvin Rajkomar, Claire Cui, Andrew M. Dai

Time series data are prevalent in electronic health records, mostly in the form of physiological parameters such as vital signs and lab tests.

Mortality Prediction Time Series +1

Explaining an increase in predicted risk for clinical alerts

no code implementations10 Jul 2019 Michaela Hardt, Alvin Rajkomar, Gerardo Flores, Andrew Dai, Michael Howell, Greg Corrado, Claire Cui, Moritz Hardt

We consider explanations in a temporal setting where a stateful dynamical model produces a sequence of risk estimates given an input at each time step.

Attribute

Learning the Graphical Structure of Electronic Health Records with Graph Convolutional Transformer

2 code implementations11 Jun 2019 Edward Choi, Zhen Xu, Yujia Li, Michael W. Dusenberry, Gerardo Flores, Yuan Xue, Andrew M. Dai

A recent study showed that using the graphical structure underlying EHR data (e. g. relationship between diagnoses and treatments) improves the performance of prediction tasks such as heart failure prediction.

Graph Reconstruction Readmission Prediction +1

Depth map estimation methodology for detecting free-obstacle navigation areas

no code implementations15 May 2019 Sergio Trejo, Karla Martinez, Gerardo Flores

To determine if there is a free space large enough for the quadrotor to pass through, our approach marks an area inside the disparity map by using the Kalman Filter output information.

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