activity
20172023
most citedAdvanced Steel Microstructural Classification by Deep Learning Methods

478 citations · 812 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CY2023★ 2 cited

Drones4Good: Supporting Disaster Relief Through Remote Sensing and AI

Nina Merkle, Reza Bahmanyar, Corentin Henry +8

In order to respond effectively in the aftermath of a disaster, emergency services and relief organizations rely on timely and accurate information about the affected areas. Remote…

cs.CV2020★ 5 cited

Multiple Pedestrians and Vehicles Tracking in Aerial Imagery: A Comprehensive Study

Seyed Majid Azimi, Maximilian Kraus, Reza Bahmanyar +1

In this paper, we address various challenges in multi-pedestrian and vehicle tracking in high-resolution aerial imagery by intensive evaluation of a number of traditional and Deep…

cs.CV2020★ 1 cited

SkyScapes -- Fine-Grained Semantic Understanding of Aerial Scenes

Seyed Majid Azimi, Corentin Henry, Lars Sommer +2

Understanding the complex urban infrastructure with centimeter-level accuracy is essential for many applications from autonomous driving to mapping, infrastructure monitoring, and…

cs.CV2020★ 4 cited

EAGLE: Large-scale Vehicle Detection Dataset in Real-World Scenarios using Aerial Imagery

Seyed Majid Azimi, Reza Bahmanyar, Corenin Henry +1

Multi-class vehicle detection from airborne imagery with orientation estimation is an important task in the near and remote vision domains with applications in traffic monitoring a…

cs.CV2020

AerialMPTNet: Multi-Pedestrian Tracking in Aerial Imagery Using Temporal and Graphical Features

Maximilian Kraus, Seyed Majid Azimi, Emec Ercelik +3

Multi-pedestrian tracking in aerial imagery has several applications such as large-scale event monitoring, disaster management, search-and-rescue missions, and as input into predic…

cs.CV2018★ 1 cited

ShuffleDet: Real-Time Vehicle Detection Network in On-board Embedded UAV Imagery

Seyed Majid Azimi

On-board real-time vehicle detection is of great significance for UAVs and other embedded mobile platforms. We propose a computationally inexpensive detection network for vehicle d…