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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 ...
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 ...
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 ...
H3DNET: A Deep Learning Framework for Hierarchical 3D Object Classification
(University of Missouri--Kansas City, 2017)
Deep learning has received a lot of attention in the fields such as speech recognition and
image classification because of the ability to learn multiple levels of features from raw data.
However, 3D deep learning is ...
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 ...
PPDQ-BG: Parallel Partition and Distributed Query Processing for Big Graphs
(University of Missouri--Kansas City, 2016)
In recent years, there has been an explosive growth of the linked data of a global
information space that often requires expensive computations to perform big graph analysis
and query processing. Graph data represent ...
CR-GAN: Content-Based Recommender System with Conditional Generative Adversarial Networks
(University of Missouri--Kansas City, 2018)
Recommender systems have become increasingly popular by providing a wide range
of products with a variety of styles. This trend has resulted in consumers expecting more
intelligent and highly dynamic recommenders. The ...
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 ...
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 ...
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 ...
3D Hand Pose Estimation Via a Lightweight Deep Learning Model
(University of Missouri -- Kansas City, 2018)
Deep Learning with depth cameras has enabled 3D hand pose estimation from RGBD
images. Commercial solutions like Leap Motion and Intel RealSense™ use stereoscopic sensors or
IR illumination-based methods to capture the ...
SAF-DL: Semantic Analysis Framework for Deep Learning Open Source Projects
(University of Missouri--Kansas City, 2018)
There are a lot of open source projects available on the internet. Specifically, due to the
increasing interest of Deep Learning (DL), the number of DL open source projects is also
increased. This project is motivated ...
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 ...
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 ...
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 ...
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 ...
Context-Aware Adaptive Model for Smart Energy
(2013)
Building energy awareness and providing feedback on energy use is a vital component in transforming the behavior of individuals and communities towards a more efficient use of electric power. An enormous amount of energy ...
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 ...
Semantic Frameworks for Document and Ontology Clustering
(University of Missouri--Kansas City, 2011-01-20)
The Internet has made it possible, in principle, for scientists to quickly find research papers of interest. In practice, the overwhelming volume of publications makes this a time consuming task. It is, therefore, important ...