Roterm: a Microprocessor Based Cipher terminal System. - Daniel Wolf (Cryptologia, 1983)

Identification and Reconstruction of Complete Gait Cycles for Person Identification in Crowded Scenes. - Martin Hofmann 011; Daniel Wolf; Gerhard Rigoll (VISAPP, 2011)

Hypergraphs for Joint Multi-view Reconstruction and Multi-object Tracking. - Martin Hofmann 011; Daniel Wolf; Gerhard Rigoll (CVPR, 2013)

RGB-D sensor setup for multiple tasks of home robots and experimental results. - Paloma de la Puente; Markus Bajones; Peter Einramhof; Daniel Wolf; David Fischinger; Markus Vincze (IROS, 2014)

Find my mug: Efficient object search with a mobile robot using semantic segmentation. - Daniel Wolf; Markus Bajones; Johann Prankl; Markus Vincze (CoRR, 2014)

Fast semantic segmentation of 3D point clouds using a dense CRF with learned parameters. - Daniel Wolf; Johann Prankl; Markus Vincze (ICRA, 2015)

Where to look first? Behaviour control for fetch-and-carry missions of service robots. - Markus Bajones; Daniel Wolf; Johann Prankl; Markus Vincze (CoRR, 2015)

Learning and Detecting Objects with a Mobile Robot to Assist Older Adults in Their Homes. - Markus Vincze; Markus Bajones; Markus Suchi; Daniel Wolf; Astrid Weiss; David Fischinger; Paloma de la Puente (ECCV Workshops (2), 2016)

Enhancing Semantic Segmentation for Robotics: The Power of 3-D Entangled Forests. - Daniel Wolf; Johann Prankl; Markus Vincze (IEEE Robotics Autom. Lett., 2016)

Multi-View 3D Entangled Forest for Semantic Segmentation and Mapping. - Morris Antonello; Daniel Wolf; Johann Prankl; Stefano Ghidoni; Emanuele Menegatti; Markus Vincze (ICRA, 2018)

Hobbit: Providing Fall Detection and Prevention for the Elderly in the Real World. - Markus Bajones; David Fischinger; Astrid Weiss; Daniel Wolf; Markus Vincze; Paloma de la Puente; Tobias Körtner; Markus Weninger; Konstantinos E. Papoutsakis; Damien Michel; Ammar Qammaz; Paschalis Panteleris; et al. (J. Robotics, 2018)

Fiducial Marker based Extrinsic Camera Calibration for a Robot Benchmarking Platform. - Timo Korthals; Daniel Wolf; Daniel Rudolph; Marc Hesse; Ulrich Rückert 001 (ECMR, 2019)

Grasping Objects From the Floor in Assistive Robotics: Real World Implications and Lessons Learned. - Paloma de la Puente; David Fischinger; Markus Bajones; Daniel Wolf; Markus Vincze (IEEE Access, 2019)

Robot Navigation in Domestic Environments: Experiences Using RGB-D Sensors in Real Homes. - Paloma de la Puente; Markus Bajones; Christian Reuther; Daniel Wolf; David Fischinger; Markus Vincze (J. Intell. Robotic Syst., 2019)

Multiple Trajectory Prediction with Deep Temporal and Spatial Convolutional Neural Networks. - Jan Strohbeck; Vasileios Belagiannis; Johannes Müller 003; Marcel Schreiber; Martin Herrmann; Daniel Wolf; Michael Buchholz (IROS, 2020)

Supervisory model predictive control for PV battery and heat pump system with phase change slurry thermal storage. - Yannik Löhr; Daniel Wolf; Clemens Pollerberg; Alexander Hörsting; Martin Mönnigmann (CoRR, 2020)

Multidimensional exact Classes, smooth Approximation and Bounded 4-Types. - Daniel Wolf (J. Symb. Log., 2020)

Results of Field Trials with a Mobile Service Robot for Older Adults in 16 Private Households. - Markus Bajones; David Fischinger; Astrid Weiss; Paloma de la Puente; Daniel Wolf; Markus Vincze; Tobias Körtner; Markus Weninger; Konstantinos E. Papoutsakis; Damien Michel; Ammar Qammaz; Paschalis Panteleris; et al. (ACM Trans. Hum. Robot Interact., 2020)

Dealing with Small Datasets for Deep Learning in Medical Imaging: An Evaluation of Self-Supervised Pre-Training on CT Scans Comparing Contrastive and Masked Autoencoder Methods for Convolutional Models. - Daniel Wolf; Tristan Payer; Catharina Silvia Lisson; Christoph Gerhard Lisson; Meinrad Beer; Timo Ropinski; Michael Götz (CoRR, 2023)

Abstract: Self-supervised Pre-training for Dealing with Small Datasets in Deep Learning for Medical Imaging - Evaluation of Contrastive and Masked Autoencoder Methods. - Daniel Wolf; Tristan Payer; Catharina Silvia Lisson; Christoph Gerhard Lisson; Meinrad Beer; Michael Götz; Timo Ropinski (Bildverarbeitung für die Medizin, 2024)

Less is More: Selective reduction of CT data for self-supervised pre-training of deep learning models with contrastive learning improves downstream classification performance. - Daniel Wolf; Tristan Payer; Catharina Silvia Lisson; Christoph Gerhard Lisson; Meinrad Beer; Michael Götz; Timo Ropinski (Comput. Biol. Medicine, 2024)

Deviation compensation in LPBF series production via statistical predeformation and structural pattern analysis. - Philipp Lechner; Christoph Hartmann 003; Daniel Wolf; Abdelrahman Habiba (J. Intell. Manuf., 2024)

Abstract: Selective Reduction of CT Data for Self-supervised Pre-training Improves Downstream Classification Performance. - Daniel Wolf; Tristan Payer; Catharina Silvia Lisson; Christoph Gerhard Lisson; Meinrad Beer; Michael Götz; Timo Ropinski (Bildverarbeitung für die Medizin, 2025)