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Fully automated classification algorithms have been successfully applied to diagnose a wide range of neurological and psychiatric diseases. They are sufficiently robust to handle data from different scanners for many applications and in specific cases outp ...
Recent studies suggest that advanced optimization based control methods such as model predictive control (MPC) can increase energy efficiency of buildings. However, adoption of these methods by industry is still slow, as building operators are used to work ...
Even though most data races are harmless, the harmful ones are at the heart of some of the worst concurrency bugs. Alas, spotting just the harmful data races in programs is like finding a needle in a haystack: 76%-90% of the true data races reported by sta ...
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Power consumption on mobile phones is a painful obstacle towards adoption of continuous sensing driven applications, e.g., continuously inferring individual’s locomotive activities (such as ‘sit’, ‘stand’ or ‘walk’) using the embedded accelerometer sensor. ...
Background: In the recent past several invasive cortical neuroprostheses have been developed. Signals recorded from the motor cortex (area MI) have been decoded and used to control computer cursors and robotic devices. Nevertheless, few attempts have been ...
We propose a semiautomatic procedure to generate land cover maps from remote sensing images. The proposed algorithm starts by building a hierarchical clustering tree, and exploits the most coherent pixels with respect to the available class information. Fo ...
Gabor features have been extensively used for facial image analysis due to their powerful representation capabilities. This paper focuses on selecting and combining multiple Gabor classifiers that are trained on, for example, different scales and local regi ...
Recent studies suggest that advanced optimization based control methods such as model predictive control (MPC) can increase energy efficiency of buildings. However, adoption of these methods by industry is still slow, as building operators are used to work ...
A Markov switching algorithm is introduced to classify attenuation measurements from telecommunication microwave links into dry and rainy periods. It is based on a simple state-space model and has the advantage of not relying on empirically estimated thres ...
Fully automated machine learning methods based on structural magnetic resonance imaging data can assist radiologists in the diagnosis of Alzheimer's disease (AD). These algorithms require large data sets to learn the separation of subjects with and without ...
