Grey-box Bayesian Optimization for Sensor Placement in Assisted Living Environments

no code implementations • 11 Sep 2023 • Shadan Golestan, Omid Ardakanian, Pierre Boulanger

Optimizing the configuration and placement of sensors is crucial for reliable fall detection, indoor localization, and activity recognition in assisted living spaces.

Activity Recognition Bayesian Optimization +1

Ischemic Stroke Lesion Prediction using imbalanced Temporal Deep Gaussian Process (iTDGP)

no code implementations • 16 Nov 2022 • Mohsen Soltanpour, Muhammad Yousefnezhad, Russ Greiner, Pierre Boulanger, Brian Buck

Due to this fact, in this article, we propose the imbalanced Temporal Deep Gaussian Process (iTDGP), a probabilistic model that can improve AIS lesions prediction by using baseline CTP time series.

Time Series Time Series Analysis

Arachnophobia Exposure Therapy using Experience-driven Procedural Content Generation via Reinforcement Learning (EDPCGRL)

no code implementations • 7 Oct 2021 • Athar Mahmoudi-Nejad, Matthew Guzdial, Pierre Boulanger

Personalized therapy, in which a therapeutic practice is adapted to an individual patient, leads to better health outcomes.

reinforcement-learning Reinforcement Learning (RL)

A New Semi-Automated Algorithm for Volumetric Segmentation of the Left Ventricle in Temporal 3D Echocardiography Sequences

no code implementations • 2 Sep 2021 • Deepa Krishnaswamy, Abhilash R. Hareendranathan, Tan Suwatanaviroj, Pierre Boulanger, Harald Becher, Michelle Noga, Kumaradevan Punithakumar

Purpose: Echocardiography is commonly used as a non-invasive imaging tool in clinical practice for the assessment of cardiac function.