1 citations · 2 across the 6 of their papers we have counts for
7 papers
CapsuleMotion: A Lightweight Real-Time Visual Motion Predictor for Capsule Endoscopy
Oliver Bause, Julia Werner, Oliver Bringmann
Video Capsule Endoscopy (VCE) is a non-invasive medical examination that allows for the observation of the small intestine, which is otherwise difficult to access. A fundamental ch…
Image Compression with Bubble-Aware Frame Rate Adaptation for Energy-Efficient Video Capsule Endoscopy
Oliver Bause, Jörg Gamerdinger, Julia Werner +1
Video Capsule Endoscopy (VCE) is a promising method for improving the medical examination of the small intestine in the gastrointestinal tract. A key challenge is their limited siz…
Reliable Mislabel Detection for Video Capsule Endoscopy Data
Julia Werner, Julius Oexle, Oliver Bause +5
The classification performance of deep neural networks relies strongly on access to large, accurately annotated datasets. In medical imaging, however, obtaining such datasets is pa…
Seeing More with Less: Video Capsule Endoscopy with Multi-Task Learning
Julia Werner, Oliver Bause, Julius Oexle +4
Video capsule endoscopy has become increasingly important for investigating the small intestine within the gastrointestinal tract. However, a persistent challenge remains the short…
Smart Video Capsule Endoscopy: Raw Image-Based Localization for Enhanced GI Tract Investigation
Oliver Bause, Julia Werner, Paul Palomero Bernardo +1
For many real-world applications involving low-power sensor edge devices deep neural networks used for image classification might not be suitable. This is due to their typically la…
Systematic Hardware Integration Testing for Smart Video-based Medical Device Prototypes
Oliver Bause, Julia Werner, Oliver Bringmann
This paper presents a hardware-in-the-loop (HIL) verification system for intelligent, camera-based in-body medical devices. A case study of a Video Capsule Endoscopy (VCE) prototyp…
A Configurable and Efficient Memory Hierarchy for Neural Network Hardware Accelerator
Oliver Bause, Paul Palomero Bernardo, Oliver Bringmann
As machine learning applications continue to evolve, the demand for efficient hardware accelerators, specifically tailored for deep neural networks (DNNs), becomes increasingly vit…