Zobrazeno 1 - 10
of 510
pro vyhledávání: '"Patel, Ankit P."'
Password-based security is prone to forgetting, guessing, and hacking. Similarly, standalone biometric-based security is susceptible to template spoofing and replay attacks. This paper proposes a biocryptosystem based on face recognition technique to
Externí odkaz:
http://arxiv.org/abs/2412.06927
Autor:
Woodland, McKell, Patel, Nihil, Castelo, Austin, Taie, Mais Al, Eltaher, Mohamed, Yung, Joshua P., Netherton, Tucker J., Calderone, Tiffany L., Sanchez, Jessica I., Cleere, Darrel W., Elsaiey, Ahmed, Gupta, Nakul, Victor, David, Beretta, Laura, Patel, Ankit B., Brock, Kristy K.
Publikováno v:
Machine.Learning.for.Biomedical.Imaging. 2 (2024) 2006
Clinically deployed deep learning-based segmentation models are known to fail on data outside of their training distributions. While clinicians review the segmentations, these models tend to perform well in most instances, which could exacerbate auto
Externí odkaz:
http://arxiv.org/abs/2408.02761
Autor:
Singh, Kaushlender, Dolui, Suman, Hegde, Bharat, Lachhvani, Lavkesh, Patel, Sharvil, Hoque, Injamul, Kumawat, Ashok K., Kumar, Ankit, Macwan, Tanmay, Raj, Harshita, Banerjee, Soumitra, Yadav, Komal, Kanik, Abha, Gautam, Pramila, Kumar, Rohit, Aich, Suman, Pradhan, Laxmikanta, Patel, Ankit, Galodiya, Kalpesh, Raju, Daniel, Jha, S. K., Jadeja, K. A., Patel, K. M., Pandya, S. N., Chaudhary, M. B., Tanna, R. L., Chattopadhyay, P. K., Pal, R., Saxena, Y. C., Sen, Abhijit, Ghosh, Joydeep
In this paper, we report the excitation of coherent density and potential fluctuations induced by magnetohydrodynamic (MHD) activity in the edge plasma region of ADITYA-U Tokamak. When the amplitude of the MHD mode, mainly the m/n = 2/1, increases be
Externí odkaz:
http://arxiv.org/abs/2407.16301
Autor:
Singh, Satpreet Harcharan, Jiang, Kevin, Bhasin, Kanchan, Sabharwal, Ashutosh, Moukaddam, Nidal, Patel, Ankit B
Semi-structured interviews (SSIs) are a commonly employed data-collection method in healthcare research, offering in-depth qualitative insights into subject experiences. Despite their value, the manual analysis of SSIs is notoriously time-consuming a
Externí odkaz:
http://arxiv.org/abs/2402.02656
Feature Extraction for Generative Medical Imaging Evaluation: New Evidence Against an Evolving Trend
Autor:
Woodland, McKell, Castelo, Austin, Taie, Mais Al, Silva, Jessica Albuquerque Marques, Eltaher, Mohamed, Mohn, Frank, Shieh, Alexander, Kundu, Suprateek, Yung, Joshua P., Patel, Ankit B., Brock, Kristy K.
Publikováno v:
MICCAI 2024. Lecture Notes in Computer Science, vol 15012. Springer, Cham (2024)
Fr\'echet Inception Distance (FID) is a widely used metric for assessing synthetic image quality. It relies on an ImageNet-based feature extractor, making its applicability to medical imaging unclear. A recent trend is to adapt FID to medical imaging
Externí odkaz:
http://arxiv.org/abs/2311.13717
Autor:
Charron, Nicholas E., Musil, Felix, Guljas, Andrea, Chen, Yaoyi, Bonneau, Klara, Pasos-Trejo, Aldo S., Venturin, Jacopo, Gusew, Daria, Zaporozhets, Iryna, Krämer, Andreas, Templeton, Clark, Kelkar, Atharva, Durumeric, Aleksander E. P., Olsson, Simon, Pérez, Adrià, Majewski, Maciej, Husic, Brooke E., Patel, Ankit, De Fabritiis, Gianni, Noé, Frank, Clementi, Cecilia
The most popular and universally predictive protein simulation models employ all-atom molecular dynamics (MD), but they come at extreme computational cost. The development of a universal, computationally efficient coarse-grained (CG) model with simil
Externí odkaz:
http://arxiv.org/abs/2310.18278
Autor:
Woodland, McKell, Patel, Nihil, Taie, Mais Al, Yung, Joshua P., Netherton, Tucker J., Patel, Ankit B., Brock, Kristy K.
Publikováno v:
In: UNSURE 2023. LNCS, vol 14291. Springer, Cham (2023)
Clinically deployed segmentation models are known to fail on data outside of their training distribution. As these models perform well on most cases, it is imperative to detect out-of-distribution (OOD) images at inference to protect against automati
Externí odkaz:
http://arxiv.org/abs/2308.03723
A key property of neural networks (both biological and artificial) is how they learn to represent and manipulate input information in order to solve a task. Different types of representations may be suited to different types of tasks, making identify
Externí odkaz:
http://arxiv.org/abs/2307.07575
Publikováno v:
Proceedings of Med-NeurIPS 2022
One barrier to the clinical deployment of deep learning-based models is the presence of images at runtime that lie far outside the training distribution of a given model. We aim to detect these out-of-distribution (OOD) images with a generative adver
Externí odkaz:
http://arxiv.org/abs/2307.10193
Training dataset biases are by far the most scrutinized factors when explaining algorithmic biases of neural networks. In contrast, hyperparameters related to the neural network architecture have largely been ignored even though different network par
Externí odkaz:
http://arxiv.org/abs/2302.03750