Ilker Bozcan

According to our database, Ilker Bozcan authored at least 9 papers between 2017 and 2021.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2021

GridNet: Image-Agnostic Conditional Anomaly Detection for Indoor Surveillance.

Ilker Bozcan, Jonas Le Fevre, Huy X. Pham, Erdal Kayacan

IEEE Robotics Autom. Lett., 2021

GateNet: An Efficient Deep Neural Network Architecture for Gate Perception Using Fish-Eye Camera in Autonomous Drone Racing.

Huy Xuan Pham, Ilker Bozcan, Andriy Sarabakha, Sami Haddadin, Erdal Kayacan

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Context-Dependent Anomaly Detection for Low Altitude Traffic Surveillance.

Ilker Bozcan, Erdal Kayacan

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

2020

UAV-AdNet: Unsupervised Anomaly Detection using Deep Neural Networks for Aerial Surveillance.

Ilker Bozcan, Erdal Kayacan

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

AU-AIR: A Multi-modal Unmanned Aerial Vehicle Dataset for Low Altitude Traffic Surveillance.

Ilker Bozcan, Erdal Kayacan

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

2019

COSMO: Contextualized scene modeling with Boltzmann Machines.

Ilker Bozcan, Sinan Kalkan

Robotics Auton. Syst., 2019

2018

CINet: A Learning Based Approach to Incremental Context Modeling in Robots.

Fethiye Irmak Dogan, Ilker Bozcan, Mehmet Celik, Sinan Kalkan

Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

What is (Missing or Wrong) in the Scene? A Hybrid Deep Boltzmann Machine for Contextualized Scene Modeling.

Ilker Bozcan, Yagmur Oymak, Idil Zeynep Alemdar, Sinan Kalkan

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

2017

A Learning Based Approach to Incremental Context Modeling in Robots.

Fethiye Irmak Dogan, Ilker Bozcan, Sinan Kalkan

CoRR, 2017