Zobrazeno 1 - 10
of 177
pro vyhledávání: '"DEMİR, UĞUR"'
Autor:
Srivastava, Philipp M., Demir, Ugur, Katsaggelos, Aggelos, Kalogera, Vicky, Teng, Elizabeth, Fragos, Tassos, Andrews, Jeff J., Bavera, Simone S., Briel, Max, Gossage, Seth, Kovlakas, Konstantinos, Kruckow, Matthias U., Liotine, Camille, Rocha, Kyle A., Sun, Meng, Xing, Zepei, Zapartas, Emmanouil
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, and gravitational-wave mergers. Binary population synthesis codes tha
Externí odkaz:
http://arxiv.org/abs/2411.02586
Autor:
Teng, Elizabeth, Demir, Ugur, Doctor, Zoheyr, Srivastava, Philipp M., Lalvani, Shamal, Kalogera, Vicky, Katsaggelos, Aggelos, Andrews, Jeff J., Bavera, Simone S., Briel, Max M., Gossage, Seth, Kovlakas, Konstantinos, Kruckow, Matthias U., Rocha, Kyle Akira, Sun, Meng, Xing, Zepei, Zapartas, Emmanouil
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 interpolating the stellar and binary properties of any system at the end of
Externí odkaz:
http://arxiv.org/abs/2410.11105
Autor:
Demir, Ugur, Jha, Debesh, Zhang, Zheyuan, Keles, Elif, Allen, Bradley, Katsaggelos, Aggelos K., Bagci, Ulas
Deployments of artificial intelligence in medical diagnostics mandate not just accuracy and efficacy but also trust, emphasizing the need for explainability in machine decisions. The recent trend in automated medical image diagnostics leans towards t
Externí odkaz:
http://arxiv.org/abs/2403.06961
Autor:
Yao, Lanhong, Zhang, Zheyuan, Demir, Ugur, Keles, Elif, Vendrami, Camila, Agarunov, Emil, Bolan, Candice, Schoots, Ivo, Bruno, Marc, Keswani, Rajesh, Miller, Frank, Gonda, Tamas, Yazici, Cemal, Tirkes, Temel, Wallace, Michael, Spampinato, Concetto, Bagci, Ulas
Intraductal Papillary Mucinous Neoplasm (IPMN) cysts are pre-malignant pancreas lesions, and they can progress into pancreatic cancer. Therefore, detecting and stratifying their risk level is of ultimate importance for effective treatment planning an
Externí odkaz:
http://arxiv.org/abs/2309.05857
Autor:
Jha, Debesh, Rauniyar, Ashish, Srivastava, Abhiskek, Hagos, Desta Haileselassie, Tomar, Nikhil Kumar, Sharma, Vanshali, Keles, Elif, Zhang, Zheyuan, Demir, Ugur, Topcu, Ahmet, Yazidi, Anis, Håakegård, Jan Erik, Bagci, Ulas
Artificial intelligence (AI) methods hold immense potential to revolutionize numerous medical care by enhancing the experience of medical experts and patients. AI-based computer-assisted diagnosis and treatment tools can democratize healthcare by mat
Externí odkaz:
http://arxiv.org/abs/2304.11530
Autor:
Zhang, Zheyuan, Wang, Bin, Yao, Lanhong, Demir, Ugur, Jha, Debesh, Turkbey, Ismail Baris, Gong, Boqing, Bagci, Ulas
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, however, it is common for models to encounter data from new and differe
Externí odkaz:
http://arxiv.org/abs/2304.02720
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 DG method taking advantage of instance-specific feature statistics co
Externí odkaz:
http://arxiv.org/abs/2212.09950
Autor:
Pattilachan, Tara M., Demir, Ugur, Keles, Elif, Jha, Debesh, Klatte, Derk, Engels, Megan, Hoogenboom, Sanne, Bolan, Candice, Wallace, Michael, Bagci, Ulas
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. We hypothesize that sub-optimal data augmentations can easily distort
Externí odkaz:
http://arxiv.org/abs/2301.02181
Autor:
Neto, Pedro C., Boutros, Fadi, Pinto, Joao Ribeiro, Damer, Naser, Sequeira, Ana F., Cardoso, Jaime S., Bengherabi, Messaoud, Bousnat, Abderaouf, Boucheta, Sana, Hebbadj, Nesrine, Erakın, Mustafa Ekrem, Demir, Uğur, Ekenel, Hazım Kemal, Vidal, Pedro Beber de Queiroz, Menotti, David
This work summarizes the IJCB Occluded Face Recognition Competition 2022 (IJCB-OCFR-2022) embraced by the 2022 International Joint Conference on Biometrics (IJCB 2022). OCFR-2022 attracted a total of 3 participating teams, from academia. Eventually,
Externí odkaz:
http://arxiv.org/abs/2208.02760
Autor:
Demir, Ugur, Zhang, Zheyuan, Wang, Bin, Antalek, Matthew, Keles, Elif, Jha, Debesh, Borhani, Amir, Ladner, Daniela, Bagci, Ulas
Publikováno v:
ICPAI 2021
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 prognosis. Although convolutional neural networks (CNNs) have become the s
Externí odkaz:
http://arxiv.org/abs/2205.10663