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Publication search results
found 45 matches
- 2024
- Artur Wysoczanski, Nabil Ettehadi, Soroush Arabshahi, Yifei Sun, Karen Hinkley Stukovsky, Karol E. Watson, MeiLan K. Han, Erin D. Michos, Alejandro P. Comellas, Eric A. Hoffman, Andrew F. Laine, R. Graham Barr, Elsa D. Angelini:
Robust deep labeling of radiological emphysema subtypes using squeeze and excitation convolutional neural networks: The MESA Lung and SPIROMICS Studies. CoRR abs/2403.00257 (2024) - Kathryn Knight, Ioana Danciu, Olga Ovchinnikova, Jacob D. Hinkle, Mayanka Chandra Shekar, Debangshu Mukherjee, Eileen McAllister, Caitlin Rizy, Kelly Cho, Amy C. Justice, Joseph Erdos, Peter Kuzmak, Lauren Costa, Yuk-Lam Ho, Reddy Madipadga, Suzanne Tamang, Ian Goethert:
VISION: Toward a Standardized Process for Radiology Image Management at the National Level. CoRR abs/2404.18842 (2024) - Mayanka Chandra Shekar, Ian Goethert, Md Inzamam Ul Haque, Benjamin McMahon, Sayera Dhaubhadel, Kathryn Knight, Joseph Erdos, Donna Reagan, Caroline Taylor, Peter Kuzmak, John Michael Gaziano, Eileen McAllister, Lauren Costa, Yuk-Lam Ho, Kelly Cho, Suzanne Tamang, Samah Fodeh-Jarad, Olga S. Ovchinnikova, Amy C. Justice, Jacob D. Hinkle, Ioana Danciu:
Domain Shift Analysis in Chest Radiographs Classification in a Veterans Healthcare Administration Population. CoRR abs/2407.21149 (2024) - 2023
- Artur Wysoczanski, Elsa D. Angelini, Yifei Sun, Benjamin M. Smith, Eric A. Hoffman, Karen Stukovsky, Matthew J. Budoff, Karol E. Watson, John Jeffrey Carr, Elizabeth C. Oelsner, R. Graham Barr, Andrew F. Laine:
Multi-View Cnn For Total Lung Volume Inference On Cardiac Computed Tomography. ISBI 2023: 1-5 - Aristeidis Tsaris, Joshua Romero, Thorsten Kurth, Jacob D. Hinkle, Hong-Jun Yoon, Feiyi Wang, Sajal Dash, Georgia D. Tourassi:
Scaling Resolution of Gigapixel Whole Slide Images Using Spatial Decomposition on Convolutional Neural Networks. PASC 2023: 2:1-2:11 - 2022
- Philipe A. Dias, Yuxin Tian, Shawn D. Newsam, Aristeidis Tsaris, Jacob D. Hinkle, Dalton D. Lunga:
Model Assumptions and Data Characteristics: Impacts on Domain Adaptation in Building Segmentation. IEEE Trans. Geosci. Remote. Sens. 60: 1-18 (2022) - Folami Alamudun, Jacob D. Hinkle, Sajal Dash, Benjamín Hernández, Aristeidis Tsaris, Hong-Jun Yoon:
Distilling Knowledge from Ensembles of Cluster-Constrained-Attention Multiple-Instance Learners for Whole Slide Image Classification. IEEE Big Data 2022: 3393-3397 - Xiao Wang, Aristeidis Tsaris, Debangshu Mukherjee, Mohamed Wahib, Peng Chen, Mark Oxley, Olga Ovchinnikova, Jacob D. Hinkle:
Image Gradient Decomposition for Parallel and Memory-Efficient Ptychographic Reconstruction. SC 2022: 8:1-8:13 - Xiao Wang, Aristeidis Tsaris, Debangshu Mukherjee, Mohamed Wahib, Peng Chen, Mark Oxley, Olga Ovchinnikova, Jacob D. Hinkle:
Image Gradient Decomposition for Parallel and Memory-Efficient Ptychographic Reconstruction. CoRR abs/2205.06327 (2022) - 2021
- Singanallur V. Venkatakrishnan, Amirkoushyar Ziabari, Jacob D. Hinkle, Andrew W. Needham, Jeffrey M. Warren, Hassina Z. Bilheux:
Convolutional neural network based non-iterative reconstruction for accelerating neutron tomography. Mach. Learn. Sci. Technol. 2(2): 25031 (2021) - David Malmgren-Hansen, Leif Toudal Pedersen, Allan Aasbjerg Nielsen, Matilde Brandt Kreiner, Roberto Saldo, Henning Skriver, John Lavelle, Jørgen Buus-Hinkler, Klaus A. Harnvig Krane:
A Convolutional Neural Network Architecture for Sentinel-1 and AMSR2 Data Fusion. IEEE Trans. Geosci. Remote. Sens. 59(3): 1890-1902 (2021) - Abhishek Kumar Dubey, Michael T. Young, Christopher B. Stanley, Dalton D. Lunga, Jacob D. Hinkle:
Computer-aided Abnormality Detection in Chest Radiographs in a Clinical Setting via Domain-adaptation. BIOIMAGING 2021: 65-72 - Aristeidis Tsaris, Jacob D. Hinkle, Dalton D. Lunga, Philipe Ambrozio Dias:
Distributed Training for High Resolution Images: A Domain and Spatial Decomposition Approach. RSDHA@SC 2021: 27-33 - Sergei V. Kalinin, Maxim A. Ziatdinov, Jacob D. Hinkle, Stephen Jesse, Ayana Ghosh, Kyle P. Kelley, Andrew R. Lupini, Bobby G. Sumpter, Rama K. Vasudevan:
Automated and Autonomous Experiment in Electron and Scanning Probe Microscopy. CoRR abs/2103.12165 (2021) - 2020
- Devanshu Agrawal, Theodore Papamarkou, Jacob D. Hinkle:
Wide Neural Networks with Bottlenecks are Deep Gaussian Processes. J. Mach. Learn. Res. 21: 175:1-175:66 (2020) - M. Todd Young, Jacob D. Hinkle, Ramakrishnan Kannan, Arvind Ramanathan:
Distributed Bayesian optimization of deep reinforcement learning algorithms. J. Parallel Distributed Comput. 139: 43-52 (2020) - Sudip K. Seal, Seung-Hwan Lim, Dali Wang, Jacob D. Hinkle, Dalton D. Lunga, Aristeidis Tsaris:
Toward Large-Scale Image Segmentation on Summit. ICPP 2020: 27:1-27:11 - Devanshu Agrawal, Theodore Papamarkou, Jacob D. Hinkle:
Wide Neural Networks with Bottlenecks are Deep Gaussian Processes. CoRR abs/2001.00921 (2020) - Abhishek Kumar Dubey, Alina Peluso, Jacob D. Hinkle, Devanshu Agarawal, Zilong Tan:
Model Reduction of Shallow CNN Model for Reliable Deployment of Information Extraction from Medical Reports. CoRR abs/2008.01572 (2020) - Abhishek Kumar Dubey, Michael T. Young, Christopher B. Stanley, Dalton D. Lunga, Jacob D. Hinkle:
Computer-aided abnormality detection in chest radiographs in a clinical setting via domain-adaptation. CoRR abs/2012.10564 (2020) - 2019
- Shang Gao, John X. Qiu, Mohammed M. Alawad, Jacob D. Hinkle, Noah Schaefferkoetter, Hong-Jun Yoon, James Blair Christian, Paul A. Fearn, Lynne Penberthy, Xiao-Cheng Wu, Linda Coyle, Georgia D. Tourassi, Arvind Ramanathan:
Classifying cancer pathology reports with hierarchical self-attention networks. Artif. Intell. Medicine 101 (2019) - Abhishek Kumar Dubey, Jacob D. Hinkle, James Blair Christian, Georgia D. Tourassi:
Extraction of Tumor Site from Cancer Pathology Reports using Deep Filters. BCB 2019: 320-327 - Mohammed M. Alawad, Shang Gao, John X. Qiu, Noah Schaefferkoetter, Jacob D. Hinkle, Hong-Jun Yoon, James Blair Christian, Xiao-Cheng Wu, Eric B. Durbin, Jong Cheol Jeong, Isaac Hands, David Rust, Georgia D. Tourassi:
Deep Transfer Learning Across Cancer Registries for Information Extraction from Pathology Reports. BHI 2019: 1-4 - Hong-Jun Yoon, John X. Qiu, James Blair Christian, Jacob D. Hinkle, Folami Alamudun, Georgia D. Tourassi:
Selective Information Extraction Strategies for Cancer Pathology Reports with Convolutional Neural Networks. INNSBDDL 2019: 89-98 - Devanshu Agrawal, Hong-Jun Yoon, Georgia D. Tourassi, Jacob D. Hinkle:
Computer-aided detection using non-convolutional neural network Gaussian processes. Medical Imaging: Computer-Aided Diagnosis 2019: 109503N - 2018
- Alberto de la Calle, Jim Hinkley, Paul Scott, John Pye:
SolarTherm: A New Modelica Library and Simulation Platform for Concentrating Solar Thermal Power Systems. Simul. Notes Eur. 28(3): 101-103 (2018) - Chadwin D. Young, Pavel Bolshakov, Rodolfo A. Rodriguez-Davila, Peng Zhao, Ava Khosravi, Israel Mejia, Manuel Quevedo-Lopez, Christopher L. Hinkle, Robert M. Wallace:
Electrical characterization of process induced effects on non-silicon devices. ICICDT 2018: 173-176 - M. Todd Young, Jacob D. Hinkle, Arvind Ramanathan, Ramakrishnan Kannan:
HyperSpace: Distributed Bayesian Hyperparameter Optimization. SBAC-PAD 2018: 339-347 - 2017
- Alan Rolf Mickelson, Rick Wallace Kenyon, Bennett Miller, Heinz Ulrich Boehmer Fiehn, Mark Hinkle, Kaitlin Yahime Mazotti, Stefano Costa, Nicholas Bollen, Chris Dizon:
University of Colorado at boulder WiLDNet testbed. GHTC 2017: 1-9 - Prasanna Muralidharan, Jacob D. Hinkle, P. Thomas Fletcher:
A map estimation algorithm for Bayesian polynomial regression on riemannian manifolds. ICIP 2017: 215-219
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