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Skip to Search Results- 2Abdi Oskouie, Mina
- 2Chowdhury, Md Solimul
- 2Chubak, Pirooz
- 2Rabbany khorasgani, Reihaneh
- 2Sacharuk, Edward, 1948-
- 2Sharifi, AmirAli
- 54Machine Learning
- 48Reinforcement Learning
- 37Artificial Intelligence
- 31Machine learning
- 20Image processing. Digital techniques.
- 18Artificial intelligence
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Spring 2014
Counting unique number of people in a video (i.e., counting a person only once while the person passes through the field of view (FOV)), is required in many video analytic applications, such as transit passenger and pedestrian volume count in railway stations, malls and road intersections, aid...
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Fall 2013
Many clustering techniques require parameter settings and depending on an algorithms sensitivity to the parameter, the choice of the parameter value can be very important. Several approaches have been proposed to find the “best” value of the clustering parameter for the different unsupervised...
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Fall 2009
Sensor technologies are improving fast: sensors are being developed to record more types of phe- nomena in improving precisions, and they are becoming less expensive. The vision is that sensor networks deployed across large spaces, attached to important infrastructure, and embedded in our...
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Fall 2015
Transceiver duty-cycling (DC) is a popular technique to conserve energy in a wireless sensor network (WSN). In this thesis, our overall objective is to study the performance of a DC WSN. Namely, we consider the performance of a DC WSN from the point of throughput, as well as energy consumption,...
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Fall 2010
With the emergence of a new service delivery model, Software-as-a-Service (SaaS), interest in quality management in the planning and operation of SaaS systems is increasing significantly. Most current quality management approaches for SaaS focus primarily on the perspective of service provider....
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Fall 2013
With the development of globalization, numerous tele-conferencing systems have been developed to shorten the distance between people. Tele-presence is one of these systems which can broadcast high-quality audio and video to remote sites trying to give the illusion to the participants that they...
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A Study of Ensemble Machine Learning Model Architectures for Parkinson’s Disease Detection and Freezing of Gait Forecasting
DownloadFall 2021
Parkinson's Disease (PD) is a major progressive neurological disorder and is extremely difficult to diagnose PD~\cite{pmid23039866} since there are no defined medical tests for this task. The existing approach involves a combination physical examinations, neuroimaging and demographic analysis...
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Fall 2009
Stereopsis is the process of inferring the distance to objects from two or more images. It has applications in areas such as: novel-view rendering, motion capture, autonomous navigation, and topographical mapping from remote sensing data. Although it sounds simple, in light of the effortlessness...
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Fall 2018
One-class classification is a problem that arises in situations where we have data available that describes objects belonging to a particular class but very little or no data describing objects that do not belong to this class, where we must then be able to classify new data objects according to...
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Fall 2009
Associative classification is a rule-based approach to classify data relying on association rule mining by discovering associations between a set of features and a class label. Support and confidence are the de-facto “interestingness measures” used for discovering relevant association rules. The...