Ehsan Nazerfard

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The increasing aging population has inspired many machine learning researchers to find innovative solutions for assisted living. A problem often encountered in assisted living settings is activity recognition. Although activity recognition has been vastly studied by many researchers, the temporal features that constitute an activity usually have been(More)
In spite of the significant work that has been done to discover and recognize activities in the smart home research , less attention has been paid to predict the future activities that the resident is likely to perform. An activity prediction module can play a major role in design of a smart home. For instance, by taking advantage of an activity prediction(More)
One of the most common functions of smart environments is to monitor and assist older adults with their activities of daily living. Activity recognition is a key component in this application. It is essentially a temporal classification problem which has been modeled in the past by naïve Bayes classifiers and hidden Markov models (HMMs). In this paper,(More)
—An important problem that arises during the data mining process in many new emerging application domains is mining data with temporal dependencies. One such application domain is activity discovery and recognition. Activity discovery and recognition is used in many real world systems, such as assisted living and security systems, and it has been vastly(More)
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