Search Results for author: Omid Nejati Manzari

Found 6 papers, 3 papers with code

Traffic Sign Recognition Using Local Vision Transformer

no code implementations11 Nov 2023 Ali Farzipour, Omid Nejati Manzari, Shahriar B. Shokouhi

The experimental evaluations demonstrate that the hybrid network with the locality module outperforms pure transformer-based models and some of the best convolutional networks in accuracy.

Self-Driving Cars Traffic Sign Recognition

Distilling Knowledge from CNN-Transformer Models for Enhanced Human Action Recognition

no code implementations2 Nov 2023 Hamid Ahmadabadi, Omid Nejati Manzari, Ahmad Ayatollahi

The teacher model extracts local image features, whereas the student model focuses on global features using an attention mechanism.

Action Recognition Knowledge Distillation +1

Dilated-UNet: A Fast and Accurate Medical Image Segmentation Approach using a Dilated Transformer and U-Net Architecture

1 code implementation22 Apr 2023 Davoud Saadati, Omid Nejati Manzari, Sattar Mirzakuchaki

Medical image segmentation is crucial for the development of computer-aided diagnostic and therapeutic systems, but still faces numerous difficulties.

Image Segmentation Medical Image Segmentation +2

Robust Transformer with Locality Inductive Bias and Feature Normalization

1 code implementation27 Jan 2023 Omid Nejati Manzari, Hossein Kashiani, Hojat Asgarian Dehkordi, Shahriar Baradaran Shokouhi

In this paper, we explore the robustness of vision transformers against adversarial perturbations and try to enhance their robustness/accuracy trade-off in white box attack settings.

Inductive Bias Traffic Sign Recognition

Pyramid Transformer for Traffic Sign Detection

no code implementations13 Jul 2022 Omid Nejati Manzari, Amin Boudesh, Shahriar B. Shokouhi

The results demonstrate the superiority of the proposed model in the traffic sign detection tasks.

Inductive Bias Self-Driving Cars +1

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