The Department of Computer Science and Electrical Engineering (CSEE) offers bachelor’s degrees in computer science, electrical computer engineering, and information technology. We also have master’s degrees in both Electrical Engineering and Computer Science. CSEE participates in the UMKC Interdisciplinary Ph.D. program.

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Recent Submissions

  • Smart City Open Data Network System: Openness, Security, and Privacy 

    Almansoori, Mohammed (University of Missouri--Kansas City, 2017)
    The increasing concentration of population around the cities poses challenges in their operation and services. On the other hand, the current technological revolution allows scalable and innovative means to better serve ...
  • Assessment Of Overcurrent Relay Coordination In A Microgrid With High PV Penetration Deployment 

    Alshmoos, Ameer (University of Missouri--Kansas City, 2017)
    The existing distribution system is experiencing radical changes with the rapid proliferation of Distributed Energy Resources (DERs)[1]. Microgrids have been proposed as a way of integrating large numbers of distributed ...
  • Fog Computing Based IoT Applications and Their Performance 

    Gundala Palle, Santosh Reddy (University of Missouri--Kansas City, 2018)
    Today’s Internet of Things (IoT) is enabling innovations much faster to enhance the quality of life using various IoT applications such as Smart City, Smart Homes, Autonomous Driving Cars, Drone Monitoring Systems and ...
  • Smart Travel Recommender System 

    Ahmad, Bilal (University of Missouri--Kansas City, 2018)
    Many people around the globe live in areas that have unhealthy levels of air pollution. Such air pollution raises the risks of health problems. Current travel guidance systems such as Google Maps give recommendations ...
  • CR-GAN: Content-Based Recommender System with Conditional Generative Adversarial Networks 

    Vundela, Karthik Reddy (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 ...
  • SAF-DL: Semantic Analysis Framework for Deep Learning Open Source Projects 

    Tripathi, Rashmi (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 ...
  • Deep Learning for Semi-Automated Brain Claustrum Segmentation on Magnetic Resonance (MR) Images 

    Albishri, Ahmed Awad H. (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 ...
  • Framework for Automatic Identification of Paper Watermarks with Chain Codes 

    Doynov, Plamen (University of Missouri--Kansas City, 2017)
    In this dissertation, I present a new framework for automated description, archiving, and identification of paper watermarks found in historical documents and manuscripts. The early manufacturers of paper have introduced ...
  • Point Cloud Compression and Low Latency Streaming 

    Ainala, Karthik (University of Missouri--Kansas City, 2017)
    With the commoditization of the 3D depth sensors, we can now very easily model real objects and scenes into digital domain which then can be used for variety of application in gaming, animation, virtual reality, immersive ...
  • Context Based Multi-Image Visual Question Answering (VQA) in Deep Learning 

    Peddinti, Sudhakar Reddy (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 ...
  • One-Shot Learning Model for Cancer Diagnosis from Histopathological Images 

    Yarlagadda, Dig Vijay Kumar (University of Missouri--Kansas City, 2017)
    Cancer diagnosis from tissue biomarker scoring is a vital technique used in determining type and grade of cancer. This is a significant part of workload for pathologists, the process is tedious, time consuming, subjective, ...
  • Topic-Based Video Classification and Retrieval Using Machine Learning 

    Vadlamudi, Naga Krishna (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 ...
  • Study of QoE for DASH at Sub-representational Level 

    Swamy, Deepthi Basavapatna Narayana (University of Missouri--Kansas City, 2017)
    Dynamic Adaptive Streaming over HTTP has become the most commonly used technology in video streaming. It enables the player to adapt to the bitrate of the video while streaming to ensure continuous playback. DASH ...
  • H3DNET: A Deep Learning Framework for Hierarchical 3D Object Classification 

    Patel, Marmikkumar (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 ...
  • Adaptive Routing Using SDN and NFV 

    Parab, Tejas Balkrishna (University of Missouri--Kansas City, 2017)
    In recent times, the primary focus of every ISP is to deliver high quality of service for multimedia applications. Due to ever-increasing network traffic, it is challenging for ISPs to accomplish optimal network ...
  • Advanced Design and Analysis of UWB U-slot Microstrip Patch Using Theory of Characteristic Modes 

    Khan, Mahrukh (University of Missouri--Kansas City, 2017)
    Ultra wide band is rapidly advancing as a high data rate wireless communication technology. As is the case in conventional wireless communication systems, an antenna also plays a very crucial role in UWB systems. ...
  • Numerical Simulation and Performance Optimization of Perovskite Solar Cell 

    Nanduri, Sai Naga Raghuram (University of Missouri--Kansas City, 2017)
    The organic-metal halide perovskite is emerging technology in photo voltaic solar cells. For any solar cell to get the significant efficiency depends on various design parameters such as material thickness, device ...
  • Building a Knowledge Graph for Food, Energy, and Water Systems 

    Gharibi, Mohamed (University of Missouri--Kansas City, 2017)
    A knowledge graph represents millions of facts and reliable information about people, places, and things. Several companies like Microsoft, Amazon, and Google have developed knowledge graphs to better customer experience. ...
  • NCC-EM: A hybrid framework for decision making with missing information 

    Chavakula, Varun (University of Missouri--Kansas City, 2017)
    Accounting for uncertainty is important in any data driven decision making. The popular treatment of uncertainties is to employ classical probability theory by expressing variables as random variables or processes in ...
  • Algorithms on Majority Problem 

    Tarafdar, Rajarshi (University of Missouri--Kansas City, 2017)
    The main idea of the paper to give solutions to the majority problem where we are counting the number of occurrences of the majority element more than half of the total number of the elements in the input set and also ...

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