activity
20182020
most citedPhysical Attribute Prediction Using Deep Residual Neural Networks

3 citations · 3 across the 1 of their papers we have counts for

collaborators

5 papers

cs.DM2020

New heuristics for burning graphs

Zahra Rezai Farokh, Maryam Tahmasbi, Zahra Haj Rajab Ali Tehrani +1

The concept of graph burning and burning number () of a graph G was introduced recently [1]. Graph burning models the spread of contagion (fire) in a graph in discrete time…

cs.CV2019

A New GNG Graph-Based Hand Gesture Recognition Approach

Narges Mirehi, Maryam Tahmasbi

Hand Gesture Recognition (HGR) is of major importance for Human-Computer Interaction (HCI) applications. In this paper, we present a new hand gesture recognition approach called GN…

cs.CV2019

New Graph-based Features For Shape Recognition

Narges Mirehi, Maryam Tahmasbi, Alireza Tavakoli Targhi

Shape recognition is the main challenging problem in computer vision. Different approaches and tools are used to solve this problem. Most existing approaches to object recognition…

cs.CV2018★ 3 cited

Physical Attribute Prediction Using Deep Residual Neural Networks

Rashidedin Jahandideh, Alireza Tavakoli Targhi, Maryam Tahmasbi

Images taken from the Internet have been used alongside Deep Learning for many different tasks such as: smile detection, ethnicity, hair style, hair colour, gender and age predicti…

cs.CV2018

HGR-Net: A Fusion Network for Hand Gesture Segmentation and Recognition

Amirhossein Dadashzadeh, Alireza Tavakoli Targhi, Maryam Tahmasbi +1

We propose a two-stage convolutional neural network (CNN) architecture for robust recognition of hand gestures, called HGR-Net, where the first stage performs accurate semantic seg…