Zobrazeno 61 - 70
of 7 925
pro vyhledávání: '"Patel, P. M."'
Autor:
Patel, Ketan M.
Publikováno v:
Phys. Rev. D 107, 075041 (2023)
A non-supersymmetric renormalizable $SO(10)$ model, with CP invariant Yukawa sector consisting of Lorentz scalars in $10$ and $\overline{126}$ dimensional representations, is proposed. The elemental Yukawa couplings are real due to CP symmetry. The l
Externí odkaz:
http://arxiv.org/abs/2212.04095
Generating photos satisfying multiple constraints find broad utility in the content creation industry. A key hurdle to accomplishing this task is the need for paired data consisting of all modalities (i.e., constraints) and their corresponding output
Externí odkaz:
http://arxiv.org/abs/2212.00793
Autor:
Mei, Kangfu, Patel, Vishal M.
Diffusion models have emerged as a powerful generative method for synthesizing high-quality and diverse set of images. In this paper, we propose a video generation method based on diffusion models, where the effects of motion are modeled in an implic
Externí odkaz:
http://arxiv.org/abs/2212.00235
Autor:
Zeng, Yu, Lin, Zhe, Zhang, Jianming, Liu, Qing, Collomosse, John, Kuen, Jason, Patel, Vishal M.
We propose a new framework for conditional image synthesis from semantic layouts of any precision levels, ranging from pure text to a 2D semantic canvas with precise shapes. More specifically, the input layout consists of one or more semantic regions
Externí odkaz:
http://arxiv.org/abs/2211.11742
Autor:
Patel, Ketan M., Shukla, Saurabh K.
Publikováno v:
Phy. Rev. D 107(2023)
Incorporation of the standard model Yukawa interactions in a grand unified theory (GUT) often predicts varieties of new scalars that couple to the fermions and lead to some novel observational effects. We assess such a possibility for the colour sext
Externí odkaz:
http://arxiv.org/abs/2211.11283
Autor:
Bandara, Wele Gedara Chaminda, Patel, Naman, Gholami, Ali, Nikkhah, Mehdi, Agrawal, Motilal, Patel, Vishal M.
Masked Autoencoders (MAEs) learn generalizable representations for image, text, audio, video, etc., by reconstructing masked input data from tokens of the visible data. Current MAE approaches for videos rely on random patch, tube, or frame-based mask
Externí odkaz:
http://arxiv.org/abs/2211.09120
Automatic Target Recognition (ATR) is a category of computer vision algorithms which attempts to recognize targets on data obtained from different sensors. ATR algorithms are extensively used in real-world scenarios such as military and surveillance
Externí odkaz:
http://arxiv.org/abs/2211.05883
In recent years, deep neural network-based restoration methods have achieved state-of-the-art results in various image deblurring tasks. However, one major drawback of deep learning-based deblurring networks is that large amounts of blurry-clean imag
Externí odkaz:
http://arxiv.org/abs/2209.09498
Modern-day surveillance systems perform person recognition using deep learning-based face verification networks. Most state-of-the-art facial verification systems are trained using visible spectrum images. But, acquiring images in the visible spectru
Externí odkaz:
http://arxiv.org/abs/2209.08814
Although many long-range imaging systems are designed to support extended vision applications, a natural obstacle to their operation is degradation due to atmospheric turbulence. Atmospheric turbulence causes significant degradation to image quality
Externí odkaz:
http://arxiv.org/abs/2208.11284