Browsing School of Computing and Engineering (UMKC) by Thesis Advisor "Lee, Yugyung, 1960-"
Now showing items 1-20 of 63
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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 ... -
A Novel Deep Learning-Based Framework for Context Aware Semantic Segmentation in Medical Imaging
(2023)Deep learning has an enormous impact on medical image analysis. Many computer-aided diagnostic systems equipped with deep networks are rapidly reducing human intervention in healthcare. Among several applications, medical ... -
Active Mobile Interface for smart health
(2013)Computer interfaces are rapidly evolving beyond the traditional keyboard-mouse-monitor triad. The widespread availability of touch screens and voice recognition software has made it possible to execute commands in many ... -
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 ... -
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 ... -
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 ... -
Automated End-to-End Management of the Deep Learning Lifecycle
(2020)Deep learning has improved the state-of-the-art results in an ever-growing number of domains. This success heavily relies on the development of deep learning models--an experimental, iterative process that produces tens ... -
Class Representative Projection for Text-based Zero-Shot Learning
(2020)There have been significant advances in supervised machine learning and enormous benefits from deep learning for a range of diverse applications. Despite the success of deep learning, in reality, very few works have shown ... -
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 ... -
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 ... -
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 ... -
CSISE: cloud-based semantic image search engine
(2014-03-27)Due to rapid exponential growth in data, a couple of challenges we face today are how to handle big data and analyze large data sets. An IBM study showed the amount of data created in the last two years alone is 90% of the ... -
Decision Support System for Pull Requests Review Using Path-based Network Portrait Divergence and Visualization
(2022)Pull requests are widely used in open-source and industrial environments to contribute and assess contributions. Unlike the typical code review process, pull requests provide a more lightweight approach for committing, ... -
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 ... -
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 ... -
Deep Open Representative Learning for Image and Text Classification
(2020)An essential goal of artificial intelligence is to support the knowledge discovery process from data to the knowledge that is useful in decision making. The challenges in the knowledge discovery process are typically due ... -
DeepSampling: Image Sampling Technique for Cost-Effective Deep Learning
(2020)Deep learning is beneficial from big data while facing computationally expensive, with an increase in data size. Some severe data issues, such as the presence of highly skewed, sparse, and imbalanced data, would substantially ... -
Design of Multi-modality Deep Fusion Architecture for Deep Acoustic Analytics
(2021)There is increasing attention for audio classification research to support various emerging applications, including environmental monitoring, health care, and smart city. Audio classification is an important area of research ... -
Distributed Collaborative Framework for Deep Learning in Object Detection
(2020)Object detection has gained much attention in recent years because of its ability to localize and classify the objects in videos and images that can be incorporated into many applications. Traditional object detection ... -
Distributed RDF query processing and reasoning for big data / linked data
(2014-08-27)The Linked Data Movement is aimed at converting unstructured and semi-structured data on the documents to semantically connected documents called the "web of data." This is based on Resource Description Framework (RDF) ...