Search Results for author: Hatem A. Rashwan

Found 15 papers, 5 papers with code

GCNDepth: Self-supervised Monocular Depth Estimation based on Graph Convolutional Network

1 code implementation13 Dec 2021 Armin Masoumian, Hatem A. Rashwan, Saddam Abdulwahab, Julian Cristiano, Domenec Puig

In particular, our method provided comparable and promising results with a high prediction accuracy of 89% on the publicly KITTI and Make3D datasets along with a reduction of 40% in the number of trainable parameters compared to the state of the art solutions.

3D Reconstruction Depth Prediction +1

Designing and Analyzing the PID and Fuzzy Control System for an Inverted Pendulum

no code implementations9 Nov 2021 Armin Masoumian, Pezhman kazemi, Mohammad Chehreghani Montazer, Hatem A. Rashwan, Domenec Puig Valls

The inverted pendulum is a non-linear unbalanced system that needs to be controlled using motors to achieve stability and equilibrium.

Absolute distance prediction based on deep learning object detection and monocular depth estimation models

1 code implementation2 Nov 2021 Armin Masoumian, David G. F. Marei, Saddam Abdulwahab, Julian Cristiano, Domenec Puig, Hatem A. Rashwan

Determining the distance between the objects in a scene and the camera sensor from 2D images is feasible by estimating depth images using stereo cameras or 3D cameras.

Monocular Depth Estimation object-detection +1

Adversarial Learning with Multiscale Features and Kernel Factorization for Retinal Blood Vessel Segmentation

no code implementations5 Jul 2019 Farhan Akram, Vivek Kumar Singh, Hatem A. Rashwan, Mohamed Abdel-Nasser, Md. Mostafa Kamal Sarker, Nidhi Pandey, Domenec Puig

In this paper, we propose an efficient blood vessel segmentation method for the eye fundus images using adversarial learning with multiscale features and kernel factorization.

SLSNet: Skin lesion segmentation using a lightweight generative adversarial network

1 code implementation1 Jul 2019 Md. Mostafa Kamal Sarker, Hatem A. Rashwan, Farhan Akram, Vivek Kumar Singh, Syeda Furruka Banu, Forhad U H Chowdhury, Kabir Ahmed Choudhury, Sylvie Chambon, Petia Radeva, Domenec Puig, Mohamed Abdel-Nasser

Thus, this article aims to achieve precise skin lesion segmentation with minimum resources: a lightweight, efficient generative adversarial network (GAN) model called SLSNet, which combines 1-D kernel factorized networks, position and channel attention, and multiscale aggregation mechanisms with a GAN model.

Image Segmentation Lesion Segmentation +2

An Efficient Solution for Breast Tumor Segmentation and Classification in Ultrasound Images Using Deep Adversarial Learning

no code implementations1 Jul 2019 Vivek Kumar Singh, Hatem A. Rashwan, Mohamed Abdel-Nasser, Md. Mostafa Kamal Sarker, Farhan Akram, Nidhi Pandey, Santiago Romani, Domenec Puig

We propose to add an atrous convolution layer to the conditional generative adversarial network (cGAN) segmentation model to learn tumor features at different resolutions of BUS images.

General Classification SSIM +1

Using Curvilinear Features in Focus for Registering a Single Image to a 3D Object

no code implementations26 Feb 2018 Hatem A. Rashwan, Sylvie Chambon, Pierre Gurdjos, Géraldine Morin, Vincent Charvillat

The results presented highlight the quality of the features detected, in term of repeatability, and also the interest of the approach for registration and pose estimation.

Pose Estimation

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