Pak Hung Chan

According to our database, Pak Hung Chan authored at least 9 papers between 2021 and 2025.

Collaborative distances:

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

2025

Raw Camera Data Object Detectors: An Optimisation for Automotive Video Processing and Transmission.

Pak Hung Chan, Chuheng Wei, Anthony Huggett, Valentina Donzella

IEEE Access, 2025

Automotive DNN-Based Object Detection in the Presence of Lens Obstruction and Video Compression.

Gabriele Baris, Boda Li, Pak Hung Chan, Carlo Alberto Avizzano, Valentina Donzella

IEEE Access, 2025

2024

REHEARSE: adveRse wEatHEr datAset for sensoRy noiSe modEls.

Yuri Poledna, Maikol Funk Drechsler, Valentina Donzella, Pak Hung Chan, Pierre Duthon, Werner Huber

Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

Influence of AVC and HEVC compression on detection of vehicles through Faster R-CNN.

Pak Hung Chan, Anthony Huggett, Georgina Souvalioti, Paul Jennings, Valentina Donzella

Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

Parametric Physics-Based Snow Model for Automotive Cameras.

Pak Hung Chan, Kurt Debattista, Valentina Donzella

Proceedings of the 2024 IEEE SENSORS, Kobe, Japan, October 20-23, 2024, 2024

2023

Semantic-Aware Video Compression for Automotive Cameras.

Yiting Wang, Pak Hung Chan, Valentina Donzella

IEEE Trans. Intell. Veh., June, 2023

Enhanced Object Detection by Integrating Camera Parameters into Raw Image-Based Faster R-CNN.

Chuheng Wei, Guoyuan Wu, Matthew J. Barth, Pak Hung Chan, Valentina Donzella, Anthony Huggett

Proceedings of the 26th IEEE International Conference on Intelligent Transportation Systems, 2023

2022

A Two-stage H.264 based Video Compression Method for Automotive Cameras.

Yiting Wang, Pak Hung Chan, Valentina Donzella

Proceedings of the 5th IEEE International Conference on Industrial Cyber-Physical Systems, 2022

2021

The data conundrum: compression of automotive imaging data and deep neural network based perception.

Pak Hung Chan, Georgina Souvalioti, Anthony Huggett, Graham Kirsch, Valentina Donzella

Proceedings of the London Imaging Meeting 2021: Imaging for Deep Learning, 2021