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Now showing items 21-33 of 33
MDRED: Multi-Modal Multi-Task Distributed Recognition for Event Detection
(University of Missouri -- Kansas City, 2018)
Understanding users’ context is essential in emerging mobile sensing applications, such
as Metal Detector, Glint Finder, Facefirst. Over the last decade, Machine Learning (ML)
techniques have evolved dramatically for ...
DMLA: A Dynamic Model-Based Lambda Architecture for Learning and Recognition of Features in Big Data
(University of Missouri--Kansas City, 2016)
Real-time event modeling and recognition is one of the major research areas that is yet to reach its fullest potential. In the exploration of a system to fit in the tremendous challenges posed by data growth, several big ...
Social Bridge: searching beyond Friend of a Friend networks
(University of Missouri--Kansas City, 2012-06-11)
Social networking has turned into an integral constituent in our lives. There appears
to be an imperative demand for finding and linking with others to share one's day-to-day
activities. However, currently available ...
Event driven querying of semantic sensor web services
(University of Missouri--Kansas City, 2012-05-15)
In today's world, there is a tremendous increase in the usage of sensor technology in several fields including agriculture, medicine, and weather. Sensors either in-site or remotely placed are usually deployed in the form ...
A Pervasive Middleware for Activity Recognition with Smartphones
(2015)
Activity Recognition (AR) is an important research topic in pervasive computing. With the rapid increase in the use of pervasive devices, huge sensor data is generated from diverse devices on a daily basis. Analysis of the ...
Feature-based Analysis for Open Source using Big Data Analytics
(2015)
The open source code base has increased enormously and hence understanding the functionality of the projects has become extremely difficult. The existing approaches of feature discovery that aim to identify functionality ...
Dynamic Model Generation and Semantic Search for Open Source Projects using Big Data Analytics
(2015)
Open source software is quite ubiquitous and caters to most common software needs developers come across. Many open source projects are considered better than their commercial equivalents as a larger pool of developers ...
Multi-Modal Topic Sentiment Analytics for Twitter
(University of Missouri -- Kansas City, 2018)
Sentiment analysis has proven to be very successful in text applications. Social media
is also considered a quite rich source to get data regarding user’s behaviors and
preference. Identifying social context would make ...
SigsSpace-Text: Parallel and Distributed Signature Learning in Text Analytics
(University of Missouri--Kansas City, 2016)
Big data analytics uncover hidden patterns and useful information from big data. It is a complex and time-consuming process. Recent advancements in parallel and distributed approaches have led to the evolution of big data ...
Topic-Based Video Classification and Retrieval Using Machine Learning
(University of Missouri--Kansas City, 2017)
Machine learning has made significant progress for many real-world problems. The
Deep Learning (DL) models proposed primarily concentrate on object detection, image
classification, and image captioning. However, very ...
Deep Learning for Semi-Automated Brain Claustrum Segmentation on Magnetic Resonance (MR) Images
(University of Missouri--Kansas City, 2018)
In recent years, Deep Learning (DL) has shown promising results with regard to
conducting AI tasks such as computer vision and speech recognition. Specifically, DL
demonstrated the state-of-the-art in computer vision ...
A semantic framework for event-driven service composition
(University of Missouri--Kansas City, 2011-09-14)
Service Oriented Architecture (SOA) has become a popular paradigm for designing
distributed systems where loosely coupled services (i.e. computational entities) can be
integrated seamlessly to provide complex composite ...
A Semantic Approach for Automatic Recovery of Software Architecture
(2014)
Open source projects have been continuously growing in popularity. As a result, a number of open source projects begin to play an important role in current software development. In practice, limited assistance has been ...