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SigSpace – Class-Based Feature Representation for Scalable and Distributed Machine Learning
(University of Missouri–Kansas City, 2016)
In the era of big data, it is essential to explore the opportunities in discovering knowledge
from big data. However, traditional machine learning approaches are not well fit
to analyze the full value of big data. ...
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 ...
AI-based Edge Computing System for Event Based Analytics
(2021)
In recent years, the Internet of Things (IoT) has received lots of attention due to its promising applications. Along with IoT evolution, we have witnessed advanced research for edge computing and its potential benefits ...
Siamese Network-Based Multi-Modal Deepfake Detection
(2020)
but maximizes the distance to negative samples. To test and validate our proposed model, we report our metrics like similarity score, loss, and accuracy on large-scale DFDC, Faceforensic++, and CelebDF datasets. We compared our method with state...
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 ...
Dynamic Model Generation and Semantic Search for Open Source Projects using Big Data Analytics
(2015)
Solr and Apache Lucene as a case study. Apache Solr is built using Apache Lucene core library. The results from Apache Solr analysis are compared to the manual evaluation of software architecture by experts. We have observed that 90% of the features...
VirtualMindTrial: An Intelligent Questionnaire System for Clinical Trail Recruitment
(University of Missouri--Kansas City, 2010)
The recruitment of human subjects for clinical trials research is a critically important step in the discovery of new cures for diseases. Volunteers are subjected to an elaborate questionnaire process in current recruitment ...
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 ...
Semantic Frameworks for Document and Ontology Clustering
(University of Missouri--Kansas City, 2011-01-20)
prototype to demonstrate the potential use of this framework, has been developed. The Open Biomedical Ontologies (OBOs) are used as a case study to illustrate the clustering technique used to identify common concepts and links. Detailed experimental results...
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 ...
RUPEE: A Big Data Approach to Indexing and Searching Protein Structures
(2021)
not based on structure alone. In the case of sequence clustering, strong structure similarities are often hidden behind cluster representatives. Existing protein structure searches that focus on better quality results often perform full pairwise protein...
Domain Playground: Extending Deep Learning Models to Open Domain Boundaries
(2021)
, existing approaches make strong assumptions about the data distribution, often requiring that the source and target domains have no category gap (e.g., they share label sets). In reality, this is rarely the case. There is a strong need for methods that can...
Distributed Collaborative Framework for Deep Learning in Object Detection
(2020)
that is designed with a single-class-single-model mechanism for multiple objects in a distributed manner. For useful grouping, we made use of the intraclass correlation from existing models during inferencing. Results from the case studies with Pascal VOC 2007...
Deep Open Representative Learning for Image and Text Classification
(2020)
. Additionally, semantic information and external information are added to CR-Graph to make the decision more capable of dealing with real-world data. The automated semantic information's ability to the graph is illustrated with a case study of biomedical...
Semantic code search and analysis
(2014-07-28)
As open source software repositories have been enormously growing, the high quality source codes have been widely available. A greater access to open source software also leads to an increase of software quality and reduces ...
Multiple-valued logic: technology and circuit implementation
(2021)
Transistor (CNTFET). A comparative analysis of the proposed designs and several state-of-the-art designs are also given in all the cases in terms of delay, total power, and power-delay-product (PDP). The simulation and analysis are performed using the H...
Multi-modal emotion detection using deep learning for interpersonal communication analytics
(2019)
In recent years, deep learning technologies have been increasingly applied to generate meaningful data for advanced research in humanities and sciences. Interpersonal communication skills are crucial to success in science. ...
Explainable AI framework through Multi-Context Multi-Dimensional Graph Neural Network
(2023)
In this research, we explored the multifaceted realm of digital communication, emphasizing social media channels such as Twitter and Reddit, complemented by conventional data-gathering techniques like focus group discussions ...
AudioCNN: Audio Event Classification With Deep Learning Based Multi-Channel Fusion Networks
(2020)
In recent years, there is growing interest in environmental sound classification with a plethora of real-world applications, especially in audio fields like speech and music. Recent research works have proven spectral ...