Zobrazeno 1 - 10
of 323
pro vyhledávání: '"Hasnat, Mohammad A."'
Autor:
Rabbi, Mohammad Shifat E, Pathan, Naqib Sad, Li, Shiying, Zhuang, Yan, Rubaiyat, Abu Hasnat Mohammad, Rohde, Gustavo K
Learning from point sets is an essential component in many computer vision and machine learning applications. Native, unordered, and permutation invariant set structure space is challenging to model, particularly for point set classification under sp
Externí odkaz:
http://arxiv.org/abs/2403.10015
Autor:
Rubaiyat, Abu Hasnat Mohammad, Thai, Duy H., Nichols, Jonathan M., Hutchinson, Meredith N., Wallen, Samuel P., Naify, Christina J., Geib, Nathan, Haberman, Michael R., Rohde, Gustavo K.
This paper presents a novel data-driven approach to identify partial differential equation (PDE) parameters of a dynamical system. Specifically, we adopt a mathematical "transport" model for the solution of the dynamical system at specific spatial lo
Externí odkaz:
http://arxiv.org/abs/2308.12259
Autor:
Gong, Le, Li, Shiying, Pathan, Naqib Sad, Shifat-E-Rabbi, Mohammad, Rohde, Gustavo K., Rubaiyat, Abu Hasnat Mohammad, Thareja, Sumati
Here we describe a new image representation technique based on the mathematics of transport and optimal transport. The method relies on the combination of the well-known Radon transform for images and a recent signal representation method called the
Externí odkaz:
http://arxiv.org/abs/2307.15339
There exist growing interests in intelligent systems for numerous medical imaging, image processing, and computer vision applications, such as face recognition, medical diagnosis, character recognition, and self-driving cars, among others. These appl
Externí odkaz:
http://arxiv.org/abs/2302.01459
Transport-based metrics and related embeddings (transforms) have recently been used to model signal classes where nonlinear structures or variations are present. In this paper, we study the geodesic properties of time series data with a generalized W
Externí odkaz:
http://arxiv.org/abs/2206.01984
Autor:
Rubaiyat, Abu Hasnat Mohammad, Li, Shiying, Yin, Xuwang, Rabbi, Mohammad Shifat E, Zhuang, Yan, Rohde, Gustavo K.
This paper presents a new end-to-end signal classification method using the signed cumulative distribution transform (SCDT). We adopt a transport-based generative model to define the classification problem. We then make use of mathematical properties
Externí odkaz:
http://arxiv.org/abs/2205.00348
Autor:
Deb, Mousumi, Roy, Shrestha, Hassan, Nadira, Chowdhury, Deepak, Sanfui, M.D. Hussain, Nandy, Preetam, Maiti, Dilip K., Chang, Mincheol, Rahaman, Mostafizur, Hasnat, Mohammad A., Bhunia, Kamalendu, Chattopadhyay, Pijush Kanti, Singha, Nayan Ranjan
Publikováno v:
In International Journal of Biological Macromolecules November 2024 280 Part 4
Autor:
Zhuang, Yan, Li, Shiying, Shifat-E-Rabbi, Mohammad, Yin, Xuwang, Rubaiyat, Abu Hasnat Mohammad, Rohde, Gustavo K.
We present a new method for face recognition from digital images acquired under varying illumination conditions. The method is based on mathematical modeling of local gradient distributions using the Radon Cumulative Distribution Transform (R-CDT). W
Externí odkaz:
http://arxiv.org/abs/2202.10642
Autor:
Rabbi, Mohammad Shifat E, Zhuang, Yan, Li, Shiying, Rubaiyat, Abu Hasnat Mohammad, Yin, Xuwang, Rohde, Gustavo K.
Deep convolutional neural networks (CNNs) are broadly considered to be state-of-the-art generic end-to-end image classification systems. However, they are known to underperform when training data are limited and thus require data augmentation strateg
Externí odkaz:
http://arxiv.org/abs/2201.02980
Autor:
Islam, Md. Nurnobi, Moushumy, Zannatul Mumtarin, Islam, Md Rakibul, Hossain, Mohammad Imran, Rahman, Mohammad Atiqur, Rahaman, Mostafizur, Aldalbahi, Ali, Uddin, Md. Tamez, Singha, Nayan Ranjan, Hasnat, Mohammad A.
Publikováno v:
In Electrochimica Acta 10 December 2024 507