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Start Over Year 2023 Keyword Deep Learning

1. Automated Construction Progress Monitoring using Image Segmentation and Building Information Models

open_access
Open Access
Author:
Jiang, Zhouqian
Title:
Automated Construction Progress Monitoring using Image Segmentation and Building Information Models
Graduate Program:
Architectural Engineering (PHD)
Keywords:
Construction Progress Monitoring
Building Information Modeling (BIM)
Computer Vision
Image Segmentation
Deep Learning
File:
Download Zhouqian_Jiang_Dissertation_Updated.pdf
Committee Members:
Rob Leicht, Major Field Member
John Messner, Chair & Dissertation Advisor
Julian Wang, Professor in Charge/Director of Graduate Studies
Yuqing Hu, Major Field Member
Yanxi Liu, Outside Unit & Field Member

2. Deep Learning Approach to Large-Scale Systems

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Restricted (Penn State Only)
Author:
Altamimi, Abdulelah Lafi
Title:
Deep Learning Approach to Large-Scale Systems
Graduate Program:
Electrical Engineering (PHD)
Keywords:
Deep Reinforcement Learning
Wildfire Mitigation
Stochastic Model Predictive Control
Classification
System Identification
Parameters Estimation
Deep Learning
Neural Network
File:
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Committee Members:
Minghui Zhu, Major Field Member
Constantino Lagoa, Chair & Dissertation Advisor
Jing Yang, Major Field Member
Kostas Papakonstantinou, Outside Unit & Field Member
Madhavan Swaminathan, Program Head/Chair

3. Applications of Deep Learning on Temporal and Graph Data Mining

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Restricted (Penn State Only)
Author:
He, Fang
Title:
Applications of Deep Learning on Temporal and Graph Data Mining
Graduate Program:
Computer Science and Engineering (PHD)
Keywords:
Temporal Data Mining
Graph Data Mining
Representation Learning
Deep Learning
File:
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Committee Members:
Kamesh Madduri, Major Field Member
Ting He, Major Field Member
Wang-Chien Lee, Chair & Dissertation Advisor
Zhen Lei, Outside Unit & Field Member
Chitaranjan Das, Program Head/Chair

4. Robotic Green Fruit Thinning for Apple Production

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Restricted (Penn State Only)
Author:
Hussain, Magni Stentoft
Title:
Robotic Green Fruit Thinning for Apple Production
Graduate Program:
Agricultural and Biological Engineering (PHD)
Keywords:
Apples
Robotic Green Fruit Thinning
End-Effector
Fruit Removal Dynamics
Machine Vision
Deep Learning
Instance Segmentation
Orientation Estimation
3D Orientation Estimation
Fruit and Stem Pairing
Fruit Clustering
Collision-Free Path Planning
Path Sequencing
Agricultural Robotics
Crop Load Management
File:
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Committee Members:
Suat Irmak, Program Head/Chair
Long He, Co-Chair & Dissertation Advisor
David Lyons, Major Field Member
James Schupp, Outside Unit & Field Member
Paul Heinemann, Co-Chair & Dissertation Advisor

5. Development And Application Of A ReaxFF Reactive Force Field For Copper And Copper Oxide Interactions With Silicon Via Neural Network Based Parameterization Methods

open_access
Open Access
Author:
Akbari Roshan, Kamyar
Title:
Development And Application Of A ReaxFF Reactive Force Field For Copper And Copper Oxide Interactions With Silicon Via Neural Network Based Parameterization Methods
Graduate Program:
Electrical Engineering (PHD)
Keywords:
ReaxFF
Force Field Developement
INDEEDopt
Optimization
Molecular Dynamics
Deep Learning
Neural Network Inversion
File:
Download Kamyar_Akbari_Roshan_-_Thesis.pdf
Committee Members:
David Miller, Co-Chair & Dissertation Advisor
Abhronil Sengupta, Major Field Member
Saptarshi Das, Outside Unit & Field Member
Seyedehaida Ebrahimi, Major Field Member
Adri van Duin, Co-Chair & Dissertation Advisor
Madhavan Swaminathan, Program Head/Chair

6. Training-Robust Design of Deep Neural Networks for Imaging and Vision

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Restricted (Penn State Only)
Author:
Yazdani, Amirsaeed
Title:
Training-Robust Design of Deep Neural Networks for Imaging and Vision
Graduate Program:
Electrical Engineering (PHD)
Keywords:
Computer Vision
Image Processing
Artificial Intelligence
Deep Learning
Neural Networks
Photoacoustic Target Localization
Image Relighting
Active Learning
Semantic Segmentation
File:
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Committee Members:
Madhavan Swaminathan, Program Head/Chair
Robert Collins, Major Field Member
William Higgins, Major Field Member
Houtan Jebelli, Outside Unit & Field Member
Vishal Monga, Chair & Dissertation Advisor

7. deep learning approaches for object tracking and motion estimation of ultrasound imaging sequences

open_access
Open Access
Author:
Alshahrani, Mohammed
Title:
deep learning approaches for object tracking and motion estimation of ultrasound imaging sequences
Graduate Program:
Computer Science and Engineering (MS)
Keywords:
Deep Learning
Object tracking
CFNet
Advanced-CFNet
File:
Download Final_submission.pdf
Committee Members:
John Sampson, Professor in Charge/Director of Graduate Studies
Mohamed Khaled Almekkawy, Thesis Advisor/Co-Advisor
William Evan Higgins, Committee Member

8. Visual Proteomics of Neuronal Growth Cones: Deep Learning Segmentation for Large Scale Analysis of Cryo-Electron Tomograms

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Restricted (Penn State Only)
Author:
Heebner, Jessica
Title:
Visual Proteomics of Neuronal Growth Cones: Deep Learning Segmentation for Large Scale Analysis of Cryo-Electron Tomograms
Graduate Program:
Biomedical Sciences (PHD)
Keywords:
cryoEM
cryoET
Deep Learning
Image Segmentation
Growth Cones
Proteomics
Actin
Cofilactin
TriC/CCT
Tomography
File:
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Committee Members:
David Degraff, Co-Chair & Outside Field Member
Richard Mailman, Outside Unit Member
Matthew Swulius, Chair & Dissertation Advisor
Maria Bewley, Major Field Member
Fang Tian, Major Field Member
Lisa Shantz, Program Head/Chair

9. Predicting Driver's Takeover Decisions in a Conditionally Automated Vehicle with Gaze Based Deep Learning Architectures

open_access
Open Access
Author:
Gupta, Shantanu
Title:
Predicting Driver's Takeover Decisions in a Conditionally Automated Vehicle with Gaze Based Deep Learning Architectures
Graduate Program:
Industrial Engineering (MS)
Keywords:
Conditionally Automated Vehicles
Machine Learning
Deep Learning
Situational Awareness
Takeover Performance
File:
Download Shantanu_Masters_Thesis.pdf
Committee Members:
Yiqi Zhang, Thesis Advisor/Co-Advisor
Vittaldas V Prabhu, Committee Member
Steven Landry, Program Head/Chair