Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Omid Nejati"'
Publikováno v:
Engineering Science and Technology, an International Journal, Vol 38, Iss , Pp 101320- (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:
https://doaj.org/article/5d491f6cc51f40e89c6dc84836740b92
Autor:
Sima SHAHROKHZADEH, Azam SOLEIMANI, Dor-Mohammad KORDI-TAMANDANI, Mohammad Hossein SANGTARASH, Omid NEJATI, Mohsen TAHERI
Publikováno v:
Iranian Journal of Public Health, Vol 49, Iss 7 (2020)
Background: Vesicoureteral reflux (VUR) disease is the most common type of urinary tract anomalies in children. Genetic risk factors may be associated with the etiology of VUR. The role of the Glutathione S‑transferases (GSTs) as multifunctional en
Externí odkaz:
https://doaj.org/article/5f91592ba82443ffbd65a21f431799f4
The accurate segmentation of medical images is critical for various healthcare applications. Convolutional neural networks (CNNs), especially Fully Convolutional Networks (FCNs) like U-Net, have shown remarkable success in medical image segmentation
Externí odkaz:
http://arxiv.org/abs/2402.08793
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
This paper presents a study on improving human action recognition through the utilization of knowledge distillation, and the combination of CNN and ViT models. The research aims to enhance the performance and efficiency of smaller student models by t
Externí odkaz:
http://arxiv.org/abs/2311.01283
Medical image segmentation is crucial for the development of computer-aided diagnostic and therapeutic systems, but still faces numerous difficulties. In recent years, the commonly used encoder-decoder architecture based on CNNs has been applied effe
Externí odkaz:
http://arxiv.org/abs/2304.11450
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
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