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Now showing items 1-11 of 11
A Pervasive Middleware for Activity Recognition with Smartphones
(2015)
of the following: (1) Filtering and Segmentation to detect different activities; (2) A human centered adaptive approach to create accurate personal models, leveraging on the existing impersonal models; (3) An activity library to serve different mobile applications...
Dynamic Activity Predictions using Graph-based Neural Networks for Time Series Forecasting
(2023)
Time series forecasting is a vital task in numerous fields, and traditional methods,
machine learning models, and neural graph networks have been employed to improve
prediction accuracy. However, these techniques need ...
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 ...
Second chance competitive autoencoders for understanding textual data
(2021)
Every day, an enormous amount of text data is produced. Sources of text data include news, social media, emails, text messages, medical reports, scientific publications, and fiction. To keep track of this data, there are ...
Deep Open Representative Learning for Image and Text Classification
(2020)
contributions in machine learning, specifically for image and text classification, i) The unique design of a latent feature vector, i.e., class representative, represents the abstract embedding space projects with the features extracted from a deep neural...
Deep Assertion discovery using word embeddings
(University of Missouri -- Kansas City, 2018)
In recent years, there has been explosive growth in the amount of biomedical data
(e.g., publications, notes from EHRs, clinical trial results), with the majority being
unstructured data. As the volume of data is ...
DL-DI: A Deep Learning Framework for Distributed, Incremental Image Classification
(University of Missouri--Kansas City, 2017)
Deep Learning technologies show promise for dramatic advances in fields such as image
classification and speech recognition. Deep Learning (DL) is a class of Machine Learning algorithms
that involves learning of multiple ...
Identifying personality and topics of social media
(2019)
on the Big 5 model. We have built the Big 5 personality classification model using a Twitter dataset that has defined openness, conscientiousness, extraversion, agreeableness, and neuroticism. In this thesis, we (1) conduct personality detection using the Big...
ADInsight: A Multimodal and Explainable Framework for Alzheimer's Disease Progression and Conversion Prediction
(2023)
ADInsight represents the crux of this dissertation, introducing an integrated and explainable framework centered on predicting Alzheimer's disease (AD) conversion, particularly for those at the early stage of mild cognitive ...
A Graph Analytics Framework for Knowledge Discovery
(2016)
In the current data movement, numerous efforts have been made to convert and normalize
a large number of traditionally structured and unstructured data to semi-structured data
(e.g., RDF, OWL). With the increasing number ...
Context Based Multi-Image Visual Question Answering (VQA) in Deep Learning
(University of Missouri--Kansas City, 2017)
Image question answering has gained huge popularity in recent years due to
advancements in Deep Learning technologies and computer processing hardware which are
able to achieve higher accuracies with faster processing ...