Fast LIDAR-based road detection using fully convolutional neural networks. - Luca Caltagirone; Samuel Scheidegger; Lennart Svensson; Mattias Wahde (Intelligent Vehicles Symposium, 2017)

Mono-Camera 3D Multi-Object Tracking Using Deep Learning Detections and PMBM Filtering. - Samuel Scheidegger; Joachim Benjaminsson; Emil Rosenberg; Amrit Krishnan; Karl Granström (Intelligent Vehicles Symposium, 2018)

Separable Convolutional Eigen-Filters (SCEF): Building Efficient CNNs Using Redundancy Analysis. - Samuel Scheidegger; Yinan Yu; Tomas McKelvey (CoRR, 2019)

A Pre-study on Data Processing Pipelines for Roadside Object Detection Systems Towards Safer Road Infrastructure. - Yinan Yu; Samuel Scheidegger; John-Fredrik Grönvall; Magnus Palm; Erik Svanberg; Johan Amoruso Wennerby; Jörg Bakker (CoRR, 2022)

climateBUG : A data-driven framework for analyzing bank reporting through a climate lens. - Yinan Yu; Samuel Scheidegger; Jasmine Elliott; Åsa Löfgren (Expert Syst. Appl., 2024)

Building efficient CNNs using Depthwise Convolutional Eigen-Filters (DeCEF). - Yinan Yu; Samuel Scheidegger; Tomas McKelvey (Neurocomputing, 2024)