activity
20182021
most citedAbsolute distance prediction based on deep learning object detection and monocular depth estimation models

41 citations · 81 across the 6 of their papers we have counts for

collaborators

15 papers

cs.RO20217 cited

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

Armin Masoumian, Pezhman kazemi, Mohammad Chehreghani Montazer +2

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

cs.RO20213 cited

Using The Feedback of Dynamic Active-Pixel Vision Sensor (Davis) to Prevent Slip in Real Time

Armin Masoumian, Pezhman kazemi, Mohammad Chehreghani Montazer +2

The objective of this paper is to describe an approach to detect the slip and contact force in real-time feedback. In this novel approach, the DAVIS camera is used as a vision tact…

cs.CV202141 cited

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

Armin Masoumian, David G. F. Marei, Saddam Abdulwahab +3

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. The outcome…

eess.IV20211 cited

AWEU-Net: An Attention-Aware Weight Excitation U-Net for Lung Nodule Segmentation

Syeda Furruka Banu, Md. Mostafa Kamal Sarker, Mohamed Abdel-Nasser +2

Lung cancer is deadly cancer that causes millions of deaths every year around the world. Accurate lung nodule detection and segmentation in computed tomography (CT) images is the m…

eess.IV20192 cited

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

Farhan Akram, Vivek Kumar Singh, Hatem A. Rashwan +4

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. In t…

eess.IV201927 cited

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

Vivek Kumar Singh, Hatem A. Rashwan, Mohamed Abdel-Nasser +5

This paper proposes an efficient solution for tumor segmentation and classification in breast ultrasound (BUS) images. We propose to add an atrous convolution layer to the conditio…