Zobrazeno 1 - 10
of 1 854
pro vyhledávání: '"Ghahremani P"'
Autor:
Jian, Bailiang, Pan, Jiazhen, Ghahremani, Morteza, Rueckert, Daniel, Wachinger, Christian, Wiestler, Benedikt
Our findings indicate that adopting "advanced" computational elements fails to significantly improve registration accuracy. Instead, well-established registration-specific designs offer fair improvements, enhancing results by a marginal 1.5\% over th
Externí odkaz:
http://arxiv.org/abs/2407.19274
Autor:
Taghipour, Ashkan, Ghahremani, Morteza, Bennamoun, Mohammed, Rekavandi, Aref Miri, Li, Zinuo, Laga, Hamid, Boussaid, Farid
This paper investigates the role of CLIP image embeddings within the Stable Video Diffusion (SVD) framework, focusing on their impact on video generation quality and computational efficiency. Our findings indicate that CLIP embeddings, while crucial
Externí odkaz:
http://arxiv.org/abs/2407.19205
In this study, we investigate a novel "dimerized" dielectric metasurface featuring dual-mode resonances governed by symmetry-protected bound states in the continuum (BICs). The metasurface design offers advantages such as insensitivity to incident li
Externí odkaz:
http://arxiv.org/abs/2406.13472
Publikováno v:
NeurIPS 2024
Controllable text-to-image (T2I) diffusion models have shown impressive performance in generating high-quality visual content through the incorporation of various conditions. Current methods, however, exhibit limited performance when guided by skelet
Externí odkaz:
http://arxiv.org/abs/2406.02485
Autor:
Ghahremani, Maryam
Biological tissues are complex structures composed of many elements which make light-based tissue diagnostics challenging. Over the past decades, Monte Carlo technique has been used as a fundamental and versatile approach toward modeling photon-tissu
Externí odkaz:
http://arxiv.org/abs/2405.06810
Autor:
Ghahremani, Tanaz, Hoseyni, Mohammad, Ahmadi, Mohammad Javad, Mehrabi, Pouria, Nikoofard, Amirhossein
Data augmentation is a key technique for addressing the challenge of limited datasets, which have become a major component in the training procedures of image processing. Techniques such as geometric transformations and color space adjustments have b
Externí odkaz:
http://arxiv.org/abs/2405.04442
Existing pose estimation models perform poorly on wheelchair users due to a lack of representation in training data. We present a data synthesis pipeline to address this disparity in data collection and subsequently improve pose estimation performanc
Externí odkaz:
http://arxiv.org/abs/2404.17063
This study presents a novel approach to activate a narrowband transparency line within a reflecting broadband window in all-dielectric metasurfaces, in analogy to the electromagnetically-induced transparency effect, by means of a quasi-bound state in
Externí odkaz:
http://arxiv.org/abs/2404.12200
Autor:
Ghahremani, Behzad, Babaee, Hessam
We present a novel tensor interpolation algorithm for the time integration of nonlinear tensor differential equations (TDEs) on the tensor train and Tucker tensor low-rank manifolds, which are the building blocks of many tensor network decompositions
Externí odkaz:
http://arxiv.org/abs/2403.12826
Autor:
Taghipour, Ashkan, Ghahremani, Morteza, Bennamoun, Mohammed, Rekavandi, Aref Miri, Laga, Hamid, Boussaid, Farid
While latent diffusion models (LDMs) excel at creating imaginative images, they often lack precision in semantic fidelity and spatial control over where objects are generated. To address these deficiencies, we introduce the Box-it-to-Bind-it (B2B) mo
Externí odkaz:
http://arxiv.org/abs/2402.17910