3 papers
cs.CV2026
StaticSegFormer: An Efficient High-Performance Semantic Segmentation Based on Static Structured Pruning
Timo Bartels, Danish Nazir, Jan Piewek +2
Structured pruning enhances the efficiency of deep neural networks (DNNs) by eliminating groups of parameters during inference. Previous methods mostly reduce computational complex…
cs.CV2026
Adversarial Attack and Disturbance Detection by Hadamard-Coded Output Representations for Object Detection and Semantic Segmentation
Lucas Görnhardt, Timo Bartels, Niklas Schwarz +1
Conventional one-hot encodings often yield poorly calibrated models, being overconfident under attack, and letting entropy-based detection algorithms fail. Previous image classific…
cs.LG2025
An Efficient Semantic Segmentation Decoder for In-Car or Distributed Applications
Danish Nazir, Gowtham Sai Inti, Timo Bartels +3
Modern automotive systems leverage deep neural networks (DNNs) for semantic segmentation and operate in two key application areas: (1) In-car, where the DNN solely operates in the…