Zobrazeno 1 - 10
of 1 269
pro vyhledávání: '"P. Shokouhi"'
Publikováno v:
Geophysical Research Letters, Vol 50, Iss 11, Pp n/a-n/a (2023)
Abstract This study focuses on unraveling the microphysical origins of the nonlinear elastic effects, which are pervasive in the Earth's crust. Here, we examine the influence of grain shape on the elastic nonlinearity of granular assemblies. We find
Externí odkaz:
https://doaj.org/article/f36e296723e249ecb6e3c0bc6b681bb5
Semantic segmentation, as a crucial component of complex visual interpretation, plays a fundamental role in autonomous vehicle vision systems. Recent studies have significantly improved the accuracy of semantic segmentation by exploiting complementar
Externí odkaz:
http://arxiv.org/abs/2407.01328
Recognition of traffic signs is a crucial aspect of self-driving cars and driver assistance systems, and machine vision tasks such as traffic sign recognition have gained significant attention. CNNs have been frequently used in machine vision, but in
Externí odkaz:
http://arxiv.org/abs/2311.06651
Fairness-related assumptions about what constitute appropriate NLG system behaviors range from invariance, where systems are expected to behave identically for social groups, to adaptation, where behaviors should instead vary across them. To illumina
Externí odkaz:
http://arxiv.org/abs/2310.15398
Autor:
Manzari, Omid Nejati, Ahmadabadi, Hamid, Kashiani, Hossein, Shokouhi, Shahriar B., Ayatollahi, Ahmad
Publikováno v:
Computers in Biology and Medicine 2023
Convolutional Neural Networks (CNNs) have advanced existing medical systems for automatic disease diagnosis. However, there are still concerns about the reliability of deep medical diagnosis systems against the potential threats of adversarial attack
Externí odkaz:
http://arxiv.org/abs/2302.09462
Autor:
Manzari, Omid Nejati, Kashiani, Hossein, Dehkordi, Hojat Asgarian, Shokouhi, Shahriar Baradaran
Publikováno v:
Engineering Science and Technology, an International Journal, 2023
Vision transformers have been demonstrated to yield state-of-the-art results on a variety of computer vision tasks using attention-based networks. However, research works in transformers mostly do not investigate robustness/accuracy trade-off, and th
Externí odkaz:
http://arxiv.org/abs/2301.11553
Traffic sign detection is a vital task in the visual system of self-driving cars and the automated driving system. Recently, novel Transformer-based models have achieved encouraging results for various computer vision tasks. We still observed that va
Externí odkaz:
http://arxiv.org/abs/2207.06067
Autor:
Arabzadeh, Negar, Ahmadvand, Ali, Kiseleva, Julia, Liu, Yang, Awadallah, Ahmed Hassan, Zhong, Ming, Shokouhi, Milad
Publikováno v:
EACL 2023
The recent increase in the volume of online meetings necessitates automated tools for managing and organizing the material, especially when an attendee has missed the discussion and needs assistance in quickly exploring it. In this work, we propose a
Externí odkaz:
http://arxiv.org/abs/2205.02370
Autor:
Liu, Ruibo, Zheng, Guoqing, Gupta, Shashank, Gaonkar, Radhika, Gao, Chongyang, Vosoughi, Soroush, Shokouhi, Milad, Awadallah, Ahmed Hassan
Pre-trained language models (LMs) have been shown to memorize a substantial amount of knowledge from the pre-training corpora; however, they are still limited in recalling factually correct knowledge given a certain context. Hence, they tend to suffe
Externí odkaz:
http://arxiv.org/abs/2204.03084
Autor:
Dehkordi, Hojat Asgarian, Nezhad, Ali Soltani, Kashiani, Hossein, Shokouhi, Shahriar Baradaran, Ayatollahi, Ahmad
In still image human action recognition, existing studies have mainly leveraged extra bounding box information along with class labels to mitigate the lack of temporal information in still images; however, preparing extra data with manual annotation
Externí odkaz:
http://arxiv.org/abs/2112.07015