2 papers
cs.CV2025
Revisiting the Evaluation of Deep Neural Networks for Pedestrian Detection
Patrick Feifel, Benedikt Franke, Frank Bonarens +3
Reliable pedestrian detection represents a crucial step towards automated driving systems. However, the current performance benchmarks exhibit weaknesses. The currently applied met…
cs.CV2021
Deployment of Deep Neural Networks for Object Detection on Edge AI Devices with Runtime Optimization
Lukas Stäcker, Juncong Fei, Philipp Heidenreich +4
Deep neural networks have proven increasingly important for automotive scene understanding with new algorithms offering constant improvements of the detection performance. However,…