3 citations · 4 across the 5 of their papers we have counts for
5 papers
Finding Dino: A Plug-and-Play Framework for Zero-Shot Detection of Out-of-Distribution Objects Using Prototypes
Poulami Sinhamahapatra, Franziska Schwaiger, Shirsha Bose +3
Detecting and localising unknown or out-of-distribution (OOD) objects in any scene can be a challenging task in vision, particularly in safety-critical cases involving autonomous s…
Spiking CenterNet: A Distillation-boosted Spiking Neural Network for Object Detection
Lennard Bodden, Franziska Schwaiger, Duc Bach Ha +2
In the era of AI at the edge, self-driving cars, and climate change, the need for energy-efficient, small, embedded AI is growing. Spiking Neural Networks (SNNs) are a promising ap…
Preventing Errors in Person Detection: A Part-Based Self-Monitoring Framework
Franziska Schwaiger, Andrea Matic, Karsten Roscher +1
The ability to detect learned objects regardless of their appearance is crucial for autonomous systems in real-world applications. Especially for detecting humans, which is often a…
Facilitating Change Implementation for Continuous ML-Safety Assurance
Chih-Hong Cheng, Nguyen Anh Vu Doan, Balahari Balu +9
We propose a method for deploying a safety-critical machine-learning component into continuously evolving environments where an increased degree of automation in the engineering pr…
From Black-box to White-box: Examining Confidence Calibration under different Conditions
Franziska Schwaiger, Maximilian Henne, Fabian Küppers +3
Confidence calibration is a major concern when applying artificial neural networks in safety-critical applications. Since most research in this area has focused on classification i…