38 citations · 63 across the 7 of their papers we have counts for
7 papers
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…
Intra-operative Brain Tumor Detection with Deep Learning-Optimized Hyperspectral Imaging
Tommaso Giannantonio, Anna Alperovich, Piercosimo Semeraro +9
Surgery for gliomas (intrinsic brain tumors), especially when low-grade, is challenging due to the infiltrative nature of the lesion. Currently, no real-time, intra-operative, labe…
N2V2 -- Fixing Noise2Void Checkerboard Artifacts with Modified Sampling Strategies and a Tweaked Network Architecture
Eva Höck, Tim-Oliver Buchholz, Anselm Brachmann +2
In recent years, neural network based image denoising approaches have revolutionized the analysis of biomedical microscopy data. Self-supervised methods, such as Noise2Void (N2V),…
Every Annotation Counts: Multi-label Deep Supervision for Medical Image Segmentation
Simon Reiß, Constantin Seibold, Alexander Freytag +2
Pixel-wise segmentation is one of the most data and annotation hungry tasks in our field. Providing representative and accurate annotations is often mission-critical especially for…
Active and Continuous Exploration with Deep Neural Networks and Expected Model Output Changes
Christoph Käding, Erik Rodner, Alexander Freytag +1
The demands on visual recognition systems do not end with the complexity offered by current large-scale image datasets, such as ImageNet. In consequence, we need curious and contin…
Seeing through bag-of-visual-word glasses: towards understanding quantization effects in feature extraction methods
Alexander Freytag, Johannes Rühle, Paul Bodesheim +2
Vector-quantized local features frequently used in bag-of-visual-words approaches are the backbone of popular visual recognition systems due to both their simplicity and their perf…
Fine-grained Categorization -- Short Summary of our Entry for the ImageNet Challenge 2012
Christoph Göring, Alexander Freytag, Erik Rodner +1
In this paper, we tackle the problem of visual categorization of dog breeds, which is a surprisingly challenging task due to simultaneously present low interclass distances and hig…