Zobrazeno 1 - 10
of 83
pro vyhledávání: '"Shirazi, Sareh"'
Autor:
Taghvaei, Amir Hossein, Mosadeghian, Farzaneh, Mosleh-Shirazi, Sareh, Ebrahimi, Azadeh, Kaňuchová, Mária, Girman, Vladimír, Bednarčík, Jozef, Khosrowpour, Zahra, Gholipourmalekabadi, Mazaher, Pahlevani, Majid
Publikováno v:
In Journal of Non-Crystalline Solids 15 February 2024 626
Autor:
Mosleh-Shirazi, Sareh, Kasaee, Seyed Reza, Dehghani, Fatemehsadat, Kamyab, Hesam, Kirpichnikova, Irina, Chelliapan, Shreeshivadasan, Firuzyar, Tahereh, Akhtari, Mohammadreza, Amani, Ali Mohammad
Publikováno v:
In Ceramics International 1 April 2023 49(7):11293-11301
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Jack, Dominic, Pontes, Jhony K., Sridharan, Sridha, Fookes, Clinton, Shirazi, Sareh, Maire, Frederic, Eriksson, Anders
Publikováno v:
Asian Conference on Computer Vision (ACCV) 2018
Representing 3D shape in deep learning frameworks in an accurate, efficient and compact manner still remains an open challenge. Most existing work addresses this issue by employing voxel-based representations. While these approaches benefit greatly f
Externí odkaz:
http://arxiv.org/abs/1803.10932
Autor:
Mirzaei, Ali, Oum, Wansik, Ham, Heon, Kwon, Yong Jung, Mosleh-Shirazi, Sareh, Shin, Ka Yoon, Yu, Dong Jae, Kang, Suk Woo, Kim, Eun Bi, Kim, Sang Sub, Kim, Hyoun Woo
Publikováno v:
In Materials Science in Semiconductor Processing October 2022 149
Autor:
Atapour, Amir, Khajehzadeh, Hossein, Shafie, Mostafa, Abbasi, Milad, Mosleh-Shirazi, Sareh, Kasaee, Seyed Reza, Amani, Ali Mohammad
Publikováno v:
In Materials Today Communications March 2022 30
Anticipating future actions is a key component of intelligence, specifically when it applies to real-time systems, such as robots or autonomous cars. While recent works have addressed prediction of raw RGB pixel values, we focus on anticipating the m
Externí odkaz:
http://arxiv.org/abs/1709.07894
We propose to learn tasks directly from visual demonstrations by learning to predict the outcome of human and robot actions on an environment. We enable a robot to physically perform a human demonstrated task without knowledge of the thought processe
Externí odkaz:
http://arxiv.org/abs/1703.02658
Publikováno v:
Robotics and Automation (ICRA), 2017 IEEE International Conference on
Deep learning models have achieved state-of-the- art performance in recognizing human activities, but often rely on utilizing background cues present in typical computer vision datasets that predominantly have a stationary camera. If these models are
Externí odkaz:
http://arxiv.org/abs/1701.04925
We propose a new task of unsupervised action detection by action matching. Given two long videos, the objective is to temporally detect all pairs of matching video segments. A pair of video segments are matched if they share the same human action. Th
Externí odkaz:
http://arxiv.org/abs/1612.00558