78,902 research outputs found
A Weakly Supervised Approach for Estimating Spatial Density Functions from High-Resolution Satellite Imagery
We propose a neural network component, the regional aggregation layer, that
makes it possible to train a pixel-level density estimator using only
coarse-grained density aggregates, which reflect the number of objects in an
image region. Our approach is simple to use and does not require
domain-specific assumptions about the nature of the density function. We
evaluate our approach on several synthetic datasets. In addition, we use this
approach to learn to estimate high-resolution population and housing density
from satellite imagery. In all cases, we find that our approach results in
better density estimates than a commonly used baseline. We also show how our
housing density estimator can be used to classify buildings as residential or
non-residential.Comment: 10 pages, 8 figures. ACM SIGSPATIAL 2018, Seattle, US
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A review of machine learning techniques in photoplethysmography for the non-invasive cuff-less measurement of blood pressure
Hypertension or high blood pressure is a leading cause of death throughout the world and a critical factor for increasing the risk of serious diseases, including cardiovascular diseases such as stroke and heart failure. Blood pressure is a primary vital sign that must be monitored regularly for the early detection, prevention and treatment of cardiovascular diseases. Traditional blood pressure measurement techniques are either invasive or cuff-based, which are impractical, intermittent, and uncomfortable for patients. Over the past few decades, several indirect approaches using photoplethysmogram (PPG) have been investigated, namely, pulse transit time, pulse wave velocity, pulse arrival time and pulse wave analysis, in an effort to utilise PPG for estimating blood pressure. Recent advancements in signal processing techniques, including machine learning and artificial intelligence, have also opened up exciting new horizons for PPG-based cuff less and continuous monitoring of blood pressure. Such a device will have a significant and transformative impact in monitoring patients’ vital signs, especially those at risk of cardiovascular disease. This paper provides a comprehensive review for non-invasive cuff-less blood pressure estimation using the PPG approach along with their challenges and limitations
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