92 citations · 133 across the 15 of their papers we have counts for
16 papers
Irregularly Sampled Time Series Interpolation for Detailed Binary Evolution Simulations
Philipp M. Srivastava, Ugur Demir, Aggelos Katsaggelos +14
Modeling of large populations of binary stellar systems is an intergral part of a many areas of astrophysics, from radio pulsars and supernovae to X-ray binaries, gamma-ray bursts,…
Emulators for stellar profiles in binary population modeling
Elizabeth Teng, Ugur Demir, Zoheyr Doctor +14
Knowledge about the internal physical structure of stars is crucial to understanding their evolution. The novel binary population synthesis code POSYDON includes a module for inter…
Explainable Transformer Prototypes for Medical Diagnoses
Ugur Demir, Debesh Jha, Zheyuan Zhang +4
Deployments of artificial intelligence in medical diagnostics mandate not just accuracy and efficacy but also trust, emphasizing the need for explainability in machine decisions. T…
Radiomics Boosts Deep Learning Model for IPMN Classification
Lanhong Yao, Zheyuan Zhang, Ugur Demir +14
Intraductal Papillary Mucinous Neoplasm (IPMN) cysts are pre-malignant pancreas lesions, and they can progress into pancreatic cancer. Therefore, detecting and stratifying their ri…
Domain Generalization with Adversarial Intensity Attack for Medical Image Segmentation
Zheyuan Zhang, Bin Wang, Lanhong Yao +5
Most statistical learning algorithms rely on an over-simplified assumption, that is, the train and test data are independent and identically distributed. In real-world scenarios, h…
A Conceptual Algorithm for Applying Ethical Principles of AI to Medical Practice
Debesh Jha, Gorkem Durak, Vanshali Sharma +12
Artificial Intelligence (AI) is poised to transform healthcare delivery through revolutionary advances in clinical decision support and diagnostic capabilities. While human experti…
A Critical Appraisal of Data Augmentation Methods for Imaging-Based Medical Diagnosis Applications
Tara M. Pattilachan, Ugur Demir, Elif Keles +7
Current data augmentation techniques and transformations are well suited for improving the size and quality of natural image datasets but are not yet optimized for medical imaging.…
Domain Generalization with Correlated Style Uncertainty
Zheyuan Zhang, Bin Wang, Debesh Jha +2
Domain generalization (DG) approaches intend to extract domain invariant features that can lead to a more robust deep learning model. In this regard, style augmentation is a strong…
Transformer based Generative Adversarial Network for Liver Segmentation
Ugur Demir, Zheyuan Zhang, Bin Wang +6
Automated liver segmentation from radiology scans (CT, MRI) can improve surgery and therapy planning and follow-up assessment in addition to conventional use for diagnosis and prog…
On Recognizing Occluded Faces in the Wild
Mustafa Ekrem Erakın, Uğur Demir, Hazım Kemal Ekenel
Facial appearance variations due to occlusion has been one of the main challenges for face recognition systems. To facilitate further research in this area, it is necessary and imp…
Information Bottleneck Attribution for Visual Explanations of Diagnosis and Prognosis
Ugur Demir, Ismail Irmakci, Elif Keles +7
Visual explanation methods have an important role in the prognosis of the patients where the annotated data is limited or unavailable. There have been several attempts to use gradi…
TinyVIRAT: Low-resolution Video Action Recognition
Ugur Demir, Yogesh S Rawat, Mubarak Shah
The existing research in action recognition is mostly focused on high-quality videos where the action is distinctly visible. In real-world surveillance environments, the actions in…
Gabriella: An Online System for Real-Time Activity Detection in Untrimmed Security Videos
Mamshad Nayeem Rizve, Ugur Demir, Praveen Tirupattur +5
Activity detection in security videos is a difficult problem due to multiple factors such as large field of view, presence of multiple activities, varying scales and viewpoints, an…
Generative Adversarial Training for MRA Image Synthesis Using Multi-Contrast MRI
Sahin Olut, Yusuf Huseyin Sahin, Ugur Demir +1
Magnetic Resonance Angiography (MRA) has become an essential MR contrast for imaging and evaluation of vascular anatomy and related diseases. MRA acquisitions are typically ordered…
Patch-Based Image Inpainting with Generative Adversarial Networks
Ugur Demir, Gozde Unal
Area of image inpainting over relatively large missing regions recently advanced substantially through adaptation of dedicated deep neural networks. However, current network soluti…
Deep Stacked Networks with Residual Polishing for Image Inpainting
Ugur Demir, Gozde Unal
Deep neural networks have shown promising results in image inpainting even if the missing area is relatively large. However, most of the existing inpainting networks introduce unde…