Aria Pezeshk

19 papers A 1B 1Misc 1Journal 6Unranked 10
YearRankTypeTitle / Venue / Authors
2023 A conf
Mapping DNN Embedding Manifolds for Network Generalization Prediction.
WACV
Molly O'Brien, Brett Wolfinger, Julia V. Bukowski, Mathias Unberath, Aria Pezeshk, Greg Hager
2022 B conf
Evaluating neural network robustness for melanoma classification using mutual information.
Image Processing
Molly O'Brien, Julia V. Bukowski, Greg Hager, Aria Pezeshk, Mathias Unberath
2022 J jnl
Mapping DNN Embedding Manifolds for Network Generalization Prediction.
CoRR
Molly O'Brien, Julia V. Bukowski, Mathias Unberath, Aria Pezeshk, Greg Hager
2021 J jnl
Test Data Reuse for the Evaluation of Continuously Evolving Classification Algorithms Using the Area under the Receiver Operating Characteristic Curve.
SIAM J. Math. Data Sci.
Alexej Gossmann, Aria Pezeshk, Yu-Ping Wang, Berkman Sahiner
2020 — conf
Lung Nodule Malignancy Classification Based ON NLSTx Data.
ISBI
Benjamin Veasey, Mohammad Mehdi Farhangi, Hichem Frigui, Justin Broadhead, Michael Dahle, Aria Pezeshk, Albert Seow, Amir A. Amini
2019 J jnl
3-D Convolutional Neural Networks for Automatic Detection of Pulmonary Nodules in Chest CT.
IEEE J. Biomed. Health Informatics
Aria Pezeshk, Sardar Hamidian, Nicholas Petrick, Berkman Sahiner
2019 — conf
Reducing overfitting of a deep learning breast mass detection algorithm in mammography using synthetic images.
Computer-Aided Diagnosis
Kenny H. Cha, Nicholas Petrick, Aria Pezeshk, Christian G. Graff, Diksha Sharma, Andreu Badal, Aldo Badano, Berkman Sahiner
2018 — conf
A database for assessment of effect of lossy compression on digital mammograms.
Image Perception, Observer Performance, and Technology Assessment
Jiheng Wang, Berkman Sahiner, Nicholas Petrick, Aria Pezeshk
2018 — conf
Test data reuse for evaluation of adaptive machine learning algorithms: over-fitting to a fixed 'test' dataset and a potential solution.
Image Perception, Observer Performance, and Technology Assessment
Alexej Gossmann, Aria Pezeshk, Berkman Sahiner
2018 — conf
Towards the use of computationally inserted lesions for mammographic CAD assessment.
Image Perception, Observer Performance, and Technology Assessment
Zahra Ghanian, Aria Pezeshk, Nicholas Petrick, Berkman Sahiner
2017 — conf
3D convolutional neural network for automatic detection of lung nodules in chest CT.
Computer-Aided Diagnosis
Sardar Hamidian, Berkman Sahiner, Nicholas Petrick, Aria Pezeshk
2017 J jnl
Seamless Lesion Insertion for Data Augmentation in CAD Training.
IEEE Trans. Medical Imaging
Aria Pezeshk, Nicholas Petrick, Weijie Chen, Berkman Sahiner
2016 — conf
Seamless lesion insertion in digital mammography: methodology and reader study.
Computer-Aided Diagnosis
Aria Pezeshk, Nicholas Petrick, Berkman Sahiner
2016 — conf
Semi-parametric estimation of the area under the precision-recall curve.
Image Perception, Observer Performance, and Technology Assessment
Berkman Sahiner, Weijie Chen, Aria Pezeshk, Nicholas Petrick
2015 — conf
Improving CAD performance by seamless insertion of pulmonary nodules in chest CT exams.
Computer-Aided Diagnosis
Aria Pezeshk, Berkman Sahiner, Weijie Chen, Nicholas Petrick
2015 J jnl
Seamless Insertion of Pulmonary Nodules in Chest CT Images.
IEEE Trans. Biomed. Eng.
Aria Pezeshk, Berkman Sahiner, Rongping Zeng, Adam Wunderlich, Weijie Chen, Nicholas Petrick
2014 — conf
Seamless insertion of real pulmonary nodules in chest CT exams.
Computer-Aided Diagnosis
Aria Pezeshk, Berkman Sahiner, Rongping Zeng, Adam Wunderlich, Weijie Chen, Nicholas Petrick
2011 J jnl
Automatic Feature Extraction and Text Recognition From Scanned Topographic Maps.
IEEE Trans. Geosci. Remote. Sens.
Aria Pezeshk, Richard L. Tutwiler
2010 Misc conf
Improved Multi Angled Parallelism for separation of text from intersecting linear features in scanned topographic maps.
ICASSP
Aria Pezeshk, Richard L. Tutwiler