activity
20182021
most citedContent-aware Density Map for Crowd Counting and Density Estimation

4 citations · 8 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20213 cited

Urban Tree Species Classification Using Aerial Imagery

Emily Waters, Mahdi Maktabdar Oghaz, Lakshmi Babu Saheer

Urban trees help regulate temperature, reduce energy consumption, improve urban air quality, reduce wind speeds, and mitigating the urban heat island effect. Urban trees also play…

cs.CV20194 cited

Content-aware Density Map for Crowd Counting and Density Estimation

Mahdi Maktabdar Oghaz, Anish R Khadka, Vasileios Argyriou +1

Precise knowledge about the size of a crowd, its density and flow can provide valuable information for safety and security applications, event planning, architectural design and to…

cs.CV2019

Scene and Environment Monitoring Using Aerial Imagery and Deep Learning

Mahdi Maktabdar Oghaz, Manzoor Razaak, Hamideh Kerdegari +2

Unmanned Aerial vehicles (UAV) are a promising technology for smart farming related applications. Aerial monitoring of agriculture farms with UAV enables key decision-making pertai…

cs.CV20191 cited

A Comparison of Embedded Deep Learning Methods for Person Detection

Chloe Eunhyang Kim, Mahdi Maktab Dar Oghaz, Jiri Fajtl +2

Recent advancements in parallel computing, GPU technology and deep learning provide a new platform for complex image processing tasks such as person detection to flourish. Person d…

cs.CV2018

Features Extraction Based on an Origami Representation of 3D Landmarks

Juan Manuel Fernandez Montenegro, Mahdi Maktab Dar Oghaz, Athanasios Gkelias +2

Feature extraction analysis has been widely investigated during the last decades in computer vision community due to the large range of possible applications. Significant work has…