Shoaib Azam

About Me

Shoaib Azam received a B.S. degree in Engineering Sciences from Ghulam Ishaq Khan Institute of Science and Technology, Pakistan, in 2010, and an M.S. degree in Robotics and Intelligent Machine Engineering from National University of Science and Technology, Pakistan, in 2015. He received his Ph.D. from Gwangju Institute of Science and Technology, Gwangju, South Korea, in 2021. In his Ph.D., he worked on the system, design, and experimental validation of autonomous vehicle in an unconstrained environment. Later, as a postdoctoral researcher, he joined Machine Learning Vision Lab, Gwangju Institute of Science and Technology, South Korea, led by Prof.Moongu Jeon, where he worked on developing end-to-end solutions using deep learning for autonomous driving and robotics. Currently, he is a postdoctoral researcher in the Intelligent Robotics Research Group led by Prof. Ville Kyrki at Aalto University, Finland. His research interest includes deep learning, autonomous driving, sensorimotor learning, and representation learning.

News

• [March 2022] Our paper Exploring Thermal Images for Object Detection in Underexposure Regions for Autonomous Driving is accepted to Applied Soft Computing (IF: 6.725).
• [March 2022] Our paper Drivable Region Estimation for Self-Driving Vehicles Using Radar is accepted to IEEE Transactions on Vehicular Technology (IF:5.978).
• [Nov 2021] Our paper ARTSeg: Employing Attention for Thermal images Semantic Segmentation is accepted to ACPR 2021.
• [June 2021] Our paper SSTN: Self-Supervised Domain Adaptation Thermal Object Detection for Autonomous Driving is accepted to IROS 2021.
• [June 2021] Our paper LDNet: End-to-End Lane Marking Detection Approach using a Dynamic Vision Sensor is accepted to IEEE Transactions on Intelligent Transportation Systems (IF:6.492).
• [May 2021] Our paper Key Points Estimation and Point Instance Segmentation Approach for Lane Detection is accepted to IEEE Transactions on Intelligent Transportation Systems (IF:6.492).
• [April 2021] Our paper Channel Boosting Feature Ensemble for Radar-based Object Detection is accepted to IV 2021.
• [Jan. 2021] Our N²C: Neural Network Controller Design Using Behavioral Cloning is accepted to IEEE Transactions on Intelligent Transportation Systems (IF:6.492).

Publications

• Exploring Thermal Images for Object Detection in Underexposure Regions for Autonomous Driving
  F. Munir, Shoaib Azam, M.A. Rafique, A.M. Sheri, M. Jeon and W. Pedrycz
  Applied Soft Computing, Elsevier. ASOC 2022.
  

• Drivable Region Estimation for Self-Driving Vehicles Using Radar
  MI. Hussain, Shoaib Azam, A. Rafiq, AM. Sheri and M. Jeon
  IEEE Transactions on Vehicular Technology. T-VT 2022.
  [PDF]

• LDNet: End-to-End Lane Marking Detection Approach using a Dynamic Vision Sensor
  Farzeen Munir, Shoaib Azam, Moongu Jeon, Byung-Geun Lee and Witold Pedrycz
  IEEE Transactions on Intelligent Transportation Systems. T-ITS 2021.
  [PDF] [Code]

• Key Points Estimation and Point Instance Segmentation Approach for Lane Detection
  Yeongmin Ko, Younkwan Lee, Shoaib Azam, Farzeen Munir, Moongu Jeon and Witold Pedrycz
  IEEE Transactions on Intelligent Transportation Systems. T-ITS 2021.
  [PDF] [Code]

• N²C: Neural Network Controller Design Using Behavioral Cloning
  Shoaib Azam, Farzeen Munir, M Aasim Rafique, A.M Sheri, M.I Hussain and Moongu Jeon
  IEEE Transactions on Intelligent Transportation Systems. T-ITS 2021.
  [PDF]

• System, Design and Experimental Validation of Autonomous Vehicle in an Unconstrained Environment
  Shoaib Azam, Farzeen Munir, A.M Sheri, J.Kim and Moongu Jeon
  Sensors. Sensors 2020.
  [PDF]

• Transfer Learning for Vehicle Detection Using Two Cameras with Different Focal Lengths
  Vinh Quang Dinh, Farzeen Munir, Shoaib Azam, Kin-Choong Yow and Moongu Jeon
  Information Sciences. Inf.Sci 2020.
  [PDF]

• Saliency Based Object Detection and Enhancements Using Spectral Residual Approach in Static Images and Videos
  Shoaib Azam, Syed Omer Gilani, Mohsin Jamil, Yasar Ayaz, Muhammad Naveed, and Muhammad Nasir Khan
  Advanced Science Letters. Adv.Sci.Lett 2015.
  

• ARTSeg: Employing Attention for Thermal images Semantic Segmentation
  Farzeen Munir, Shoaib Azam, Unse Fatima, and Moongu Jeon
  Asian Conference on Pattern Recognition (ACPR). ACPR 2021.
  

• SSTN: Self-Supervised Domain Adaptation Thermal Object Detection for Autonomous Driving
  Farzeen Munir, Shoaib Azam and Moongu Jeon
  IEEE/RSJ International Conference on Intelligent Robots and Systems. IROS 2021.
  [PDF]

• Channel Boosting Feature Ensemble for Radar-based Object Detection
  Shoaib Azam, Farzeen Munir, and Moongu Jeon
  IEEE Intelligent Vehicles Symposium. IV 2021.
  [PDF]

• Visuomotor Steering angle Prediction in Dynamic Perception Environment for Autonomous Vehicle
  Farzeen Munir, Shoaib Azam and Moongu Jeon
  IEEE International Conference On Consumer Electronics. ICCE-Asia 2020.
  [PDF]

• Multiple Objects Tracking using Radar for Autonomous Driving
  Muhamamd Ishfaq Hussain, Shoaib Azam, Farzeen Munir, Zafran Khan, and Moongu Jeon
  IEEE International IOT, Electronics and Mechatronics Conference. IEMTRONICS 2020.
  [PDF]

• Dynamic Control System Design for Autonomous Car
  Shoaib Azam, Farzeen Munir, and Moongu Jeon
  International Conference on Vehicle Technology and Intelligent Transportation Systems. VEHITS 2020.
  [PDF]

• Automated Taxi Booking Operations for Autonomous Vehicles
  Linh Van Ma, Shoaib Azam, Farzeen Munir, Jinho Choi and, Moongu Jeon
  IEEE International Conference on Signal Processing and Communication Systems. ICSPCS 2019.
  [PDF]

• Data fusion of Lidar and Thermal Camera for Autonomous driving
  Shoaib Azam, Farzeen Munir, Ahmad Muqeem Sheri, Ishfaq Hussain, YeongMin Ko and Moongu Jeon
  Applied Industrial Optics Meeting. AIO 2019.
  [PDF]

• Where Am I: Localization and 3D Maps for Autonomous Vehicles
  Farzeen Munir, Shoaib Azam, Ahmad Muqeem Sheri, YeongMin Ko and Moongu Jeon
  International Conference on Vehicle Technology and Intelligent Transportation Systems. VEHITS 2019.
  [PDF]

• Autonomous Vehicle: The Architectural Aspect of Self Driving Car
  Farzeen Munir, Shoaib Azam, Ishfaq Hussain, Ahmad Muqeem Sheri, and Moongu Jeon
  Sensors, Signal and Image Processing. SSIP 2018.
  [PDF]

• Object Modeling from 3D Point Cloud Data for Self-Driving Vehicles
  Shoaib Azam, Farzeen Munir, Aasim Rafique, YeongMin Ko, Ahmad Muqeem Sheri and Moongu Jeon
  IEEE Intelligent Vehicles Symposium. IV 2018.
  [PDF]

• Vehicle Pose Detection Using Region Based Convolutional Neural Network
  Shoaib Azam, Aasim Rafique, Moongu Jeon
  The International Conference on Control Automation & Information Science. ICCAIS 2016.
  [PDF]

• A Benchmark of Computational Models of Saliency to Predict Human Fixations in Videos
  Shoaib Azam, Syed Omer Gilani, Moongu Jeon, Rehan Yousaf, and Jeong-Bae Kim
  International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. VISGRAPP 2016.
  [PDF]

• Face-deidentification in images using restricted boltzmann machines
  Rafique, M. Aasim, Shoaib Azam, Moongu Jeon, and Sangwook Lee
  International Conference for Internet Technology and Secured Transactions. ICITST 2016.
  [PDF]

• Single object tracking system using fast compressive tracking
  Tahir, Abdullah, Shoaib Azam, Sujani Sagabala, Moongu Jeon, and Ryu Jeha
  IEEE International Conference on Consumer Electronics. ICCE-Asia 2016.
  [PDF]

Patent

• 얼굴 비식별화 방법 (Translated:”Face de-identification method”), 국내 출원 번호 : 2017-0032265, 출원일자 : 2017.03.15, 등록번호 : 10-1861520
  Rafique Muhammad Aasim, Azam Muhammad Shoaib, 최인문 (InMoon Choi), 전문구 (Moongu Jeon)
  

Reviewer Activity

• International Workshop on Assistive Computer Vision and Robotics, (ICCV), 2021
• IEEE Transactions on Intelligent Transportation Systems (IV) , 2021
• European Conference on Computer Vision (ECCV), 2020
• IEEE Transactions on Intelligent Transportation Systems (IV) , 2020
• IEEE Intelligent Transportation System Conference (ITSC), 2020
• IEEE Transaction of Intelligent Transportation Systems (T-ITS), 2020

Research Project

• Developement of Autonomous vehicle (Supported by: GIST)
  • Architecture
  • Sensor Suite
  • Demostrations
    • Complete autonomous drive
    • Demo of Obstacle Avoidance
    • Demo of Obstacle Stopping
    • Demo of Obstacle Stopping at the Entrance or Exit Gate Barrier
    • Demo of Obstacle Detection using RGB and Thermal Camera and Projection in the Lidar Frame
    • Demo of Obstacle Stopping upon detection pedestrain

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