1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CV2025
Prompt-Tuning SAM: From Generalist to Specialist with only 2048 Parameters and 16 Training Images
Tristan Piater, Björn Barz, Alexander Freytag
The Segment Anything Model (SAM) is widely used for segmenting a diverse range of objects in natural images from simple user prompts like points or bounding boxes. However, SAM's p…
stat.ML2016★ 1 cited
Maximally Divergent Intervals for Anomaly Detection
Erik Rodner, Björn Barz, Yanira Guanche +5
We present new methods for batch anomaly detection in multivariate time series. Our methods are based on maximizing the Kullback-Leibler divergence between the data distribution wi…
cs.CV2014★ 1 cited
ARTOS -- Adaptive Real-Time Object Detection System
Björn Barz, Erik Rodner, Joachim Denzler
ARTOS is all about creating, tuning, and applying object detection models with just a few clicks. In particular, ARTOS facilitates learning of models for visual object detection by…