Zobrazeno 1 - 10
of 130
pro vyhledávání: '"Azimifar, Zohreh"'
Image reconstruction is an essential step of every medical imaging method, including Photoacoustic Tomography (PAT), which is a promising modality of imaging, that unites the benefits of both ultrasound and optical imaging methods. Reconstruction of
Externí odkaz:
http://arxiv.org/abs/2404.13101
Autor:
Kamyab, Shima, Azimifar, Zohreh
In this paper, a low parameter deep learning framework utilizing the Non-metric Multi-Dimensional scaling (NMDS) method, is proposed to recover the 3D shape of 2D landmarks on a human face, in a single input image. Hence, NMDS approach is used for th
Externí odkaz:
http://arxiv.org/abs/2210.15200
In this paper we investigate a variety of deep learning strategies for solving inverse problems. We classify existing deep learning solutions for inverse problems into three categories of Direct Mapping, Data Consistency Optimizer, and Deep Regulariz
Externí odkaz:
http://arxiv.org/abs/2111.04731
Autor:
Kamyab, Shima, Azimifar, Zohreh
Publikováno v:
In Journal of Visual Communication and Image Representation February 2024 98
A lot of real-world engineering problems represent dynamicity with nests of nonlinearities due to highly complex network of exponential functions or large number of differential equations interacting together. Such search spaces are provided with mul
Externí odkaz:
http://arxiv.org/abs/1906.05516
Deep generative models are stochastic neural networks capable of learning the distribution of data so as to generate new samples. Conditional Variational Autoencoder (CVAE) is a powerful deep generative model aiming at maximizing the lower bound of t
Externí odkaz:
http://arxiv.org/abs/1903.04144
Vehicle Make and Model Recognition (MMR) systems provide a fully automatic framework to recognize and classify different vehicle models. Several approaches have been proposed to address this challenge, however they can perform in restricted condition
Externí odkaz:
http://arxiv.org/abs/1806.03028
Publikováno v:
Visual Computer; Sep2024, Vol. 40 Issue 9, p6219-6244, 26p
Autor:
Hu, Xiaodan, Naiel, Mohamed A., Azimifar, Zohreh, Ben Daya, Ibrahim, Lamm, Mark, Fieguth, Paul
Publikováno v:
In Signal Processing: Image Communication September 2021 97
In this work, we introduce a deep-structured conditional random field (DS-CRF) model for the purpose of state-based object silhouette tracking. The proposed DS-CRF model consists of a series of state layers, where each state layer spatially character
Externí odkaz:
http://arxiv.org/abs/1501.00752