Neuronale Netze

Parareal with a Learned Coarse Model for Robotic Manipulation

A key component of many robotics model-based planning and control algorithms is physics predictions, that is, forecasting a sequence of states given an initial state and a sequence of controls. This process is slow and a major computational …

A Deep Learning Approach for Pose Estimation from Volumetric OCT Data

Tracking the pose of instruments is a central problem in image-guided surgery. For microscopic scenarios, optical coherence tomography (OCT) is increasingly used as an imaging modality. OCT is suitable for accurate pose estimation due to its …

Melanoma detection with electrical impedance spectroscopy and dermoscopy using joint deep learning models

The initial assessment of skin lesions is typically based on dermoscopic images. As this is a difficult and time-consuming task, machine learning methods using dermoscopic images have been proposed to assist human experts. Other approaches have …

Left Ventricle Quantification Using Direct Regression with Segmentation Regularization and Ensembles of Pretrained 2D and 3D CNNs

Cardiac left ventricle (LV) quantification provides a tool for diagnosing cardiac diseases. Automatic calculation of all relevant LV indices from cardiac MR images is an intricate task due to large variations among patients and deformation during the …

Local monitoring of embedded applications and devices using artificial neural networks

Reliability, security, and safety become even more challenging in times of the Internet of Things (IoT). Devices operate jointly in large distributed networks and may affect each other's functionality due to failures or attacks. Identifying abnormal …

Online Monitoring of Power System Small Signal Stability Using Artificial Neural Networks

Shifting paradigms in electrical power generation, transmission and consumption will affect system dynamics and may negatively influence its small signal stability in the long run. A smaller stability margin calls for smart methods to monitor the …

Force Estimation from OCT Volumes using 3D CNNs

Purpose: Estimating the interaction forces of instruments and tissue is of interest, particularly to provide haptic feedback during robot assisted minimally invasive interventions. Different approaches based on external and integrated force sensors …