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2017


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Causal models for decision making via integrative inference

Geiger, P.

University of Stuttgart, Germany, 2017 (phdthesis)

ei

[BibTex]

2017


[BibTex]


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A Phase-coded Aperture Camera with Programmable Optics

Chen, J., Hirsch, M., Heintzmann, R., Eberhardt, B., Lensch, H. P. A.

Electronic Imaging, 2017(17):70-75, 2017 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Selective hydrogen isotope separation via breathing transition in MIL-53(Al)

Kim, J. Y., Zhang, L., Balderas-Xicohténcatl, R., Park, J., Hirscher, M., Moon, H. R., Oh, H.

{Journal of the American Chemical Society}, 139(49):17743-17746, American Chemical Society, Washington, DC, 2017 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Efficient synthesis for large-scale production and characterization for hydrogen storage of ligand exchanged MOF-74/174/184-M (M\textequalsMg2+, Ni2+)

Oh, H., Maurer, S., Balderas-Xicohténcatl, R., Arnold, L., Magdysyuk, O. V., Schütz, G., Müller, U., Hirscher, M.

{International Journal of Hydrogen Energy}, 42(2):1027-1035, Elsevier, Amsterdam, 2017 (article)

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DOI [BibTex]

DOI [BibTex]


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Capturing Hand-Object Interaction and Reconstruction of Manipulated Objects

Tzionas, D.

University of Bonn, 2017 (phdthesis)

Abstract
Hand motion capture with an RGB-D sensor gained recently a lot of research attention, however, even most recent approaches focus on the case of a single isolated hand. We focus instead on hands that interact with other hands or with a rigid or articulated object. Our framework successfully captures motion in such scenarios by combining a generative model with discriminatively trained salient points, collision detection and physics simulation to achieve a low tracking error with physically plausible poses. All components are unified in a single objective function that can be optimized with standard optimization techniques. We initially assume a-priori knowledge of the object's shape and skeleton. In case of unknown object shape there are existing 3d reconstruction methods that capitalize on distinctive geometric or texture features. These methods though fail for textureless and highly symmetric objects like household articles, mechanical parts or toys. We show that extracting 3d hand motion for in-hand scanning effectively facilitates the reconstruction of such objects and we fuse the rich additional information of hands into a 3d reconstruction pipeline. Finally, although shape reconstruction is enough for rigid objects, there is a lack of tools that build rigged models of articulated objects that deform realistically using RGB-D data. We propose a method that creates a fully rigged model consisting of a watertight mesh, embedded skeleton and skinning weights by employing a combination of deformable mesh tracking, motion segmentation based on spectral clustering and skeletonization based on mean curvature flow.

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Thesis link (url) Project Page [BibTex]


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Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art

Janai, J., Güney, F., Behl, A., Geiger, A.

Arxiv, 2017 (article)

Abstract
Recent years have witnessed amazing progress in AI related fields such as computer vision, machine learning and autonomous vehicles. As with any rapidly growing field, however, it becomes increasingly difficult to stay up-to-date or enter the field as a beginner. While several topic specific survey papers have been written, to date no general survey on problems, datasets and methods in computer vision for autonomous vehicles exists. This paper attempts to narrow this gap by providing a state-of-the-art survey on this topic. Our survey includes both the historically most relevant literature as well as the current state-of-the-art on several specific topics, including recognition, reconstruction, motion estimation, tracking, scene understanding and end-to-end learning. Towards this goal, we first provide a taxonomy to classify each approach and then analyze the performance of the state-of-the-art on several challenging benchmarking datasets including KITTI, ISPRS, MOT and Cityscapes. Besides, we discuss open problems and current research challenges. To ease accessibility and accommodate missing references, we will also provide an interactive platform which allows to navigate topics and methods, and provides additional information and project links for each paper.

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pdf Project Page Project Page [BibTex]


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A Deep Learning Based 6 Degree-of-Freedom Localization Method for Endoscopic Capsule Robots

Turan, M., Almalioglu, Y., Konukoglu, E., Sitti, M.

arXiv preprint arXiv:1705.05435, 2017 (article)

Abstract
We present a robust deep learning based 6 degrees-of-freedom (DoF) localization system for endoscopic capsule robots. Our system mainly focuses on localization of endoscopic capsule robots inside the GI tract using only visual information captured by a mono camera integrated to the robot. The proposed system is a 23-layer deep convolutional neural network (CNN) that is capable to estimate the pose of the robot in real time using a standard CPU. The dataset for the evaluation of the system was recorded inside a surgical human stomach model with realistic surface texture, softness, and surface liquid properties so that the pre-trained CNN architecture can be transferred confidently into a real endoscopic scenario. An average error of 7.1% and 3.4% for translation and rotation has been obtained, respectively. The results accomplished from the experiments demonstrate that a CNN pre-trained with raw 2D endoscopic images performs accurately inside the GI tract and is robust to various challenges posed by reflection distortions, lens imperfections, vignetting, noise, motion blur, low resolution, and lack of unique landmarks to track.

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link (url) Project Page [BibTex]


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Efficiency of analytical and sampling-based uncertainty propagation in intensity-modulated proton therapy

Wahl, N., Hennig, P., Wieser, H. P., Bangert, M.

Physics in Medicine & Biology, 62(14):5790-5807, 2017 (article)

Abstract
The sensitivity of intensity-modulated proton therapy (IMPT) treatment plans to uncertainties can be quantified and mitigated with robust/min-max and stochastic/probabilistic treatment analysis and optimization techniques. Those methods usually rely on sparse random, importance, or worst-case sampling. Inevitably, this imposes a trade-off between computational speed and accuracy of the uncertainty propagation. Here, we investigate analytical probabilistic modeling (APM) as an alternative for uncertainty propagation and minimization in IMPT that does not rely on scenario sampling. APM propagates probability distributions over range and setup uncertainties via a Gaussian pencil-beam approximation into moments of the probability distributions over the resulting dose in closed form. It supports arbitrary correlation models and allows for efficient incorporation of fractionation effects regarding random and systematic errors. We evaluate the trade-off between run-time and accuracy of APM uncertainty computations on three patient datasets. Results are compared against reference computations facilitating importance and random sampling. Two approximation techniques to accelerate uncertainty propagation and minimization based on probabilistic treatment plan optimization are presented. Runtimes are measured on CPU and GPU platforms, dosimetric accuracy is quantified in comparison to a sampling-based benchmark (5000 random samples). APM accurately propagates range and setup uncertainties into dose uncertainties at competitive run-times (GPU ##IMG## [http://ej.iop.org/images/0031-9155/62/14/5790/pmbaa6ec5ieqn001.gif] {$\leqslant {5}$} min). The resulting standard deviation (expectation value) of dose show average global ##IMG## [http://ej.iop.org/images/0031-9155/62/14/5790/pmbaa6ec5ieqn002.gif] {$\gamma_{{3}\% / {3}~{\rm mm}}$} pass rates between 94.2% and 99.9% (98.4% and 100.0%). All investigated importance sampling strategies provided less accuracy at higher run-times considering only a single fraction. Considering fractionation, APM uncertainty propagation and treatment plan optimization was proven to be possible at constant time complexity, while run-times of sampling-based computations are linear in the number of fractions. Using sum sampling within APM, uncertainty propagation can only be accelerated at the cost of reduced accuracy in variance calculations. For probabilistic plan optimization, we were able to approximate the necessary pre-computations within seconds, yielding treatment plans of similar quality as gained from exact uncertainty propagation. APM is suited to enhance the trade-off between speed and accuracy in uncertainty propagation and probabilistic treatment plan optimization, especially in the context of fractionation. This brings fully-fledged APM computations within reach of clinical application.

pn

link (url) [BibTex]

link (url) [BibTex]


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Deep EndoVO: A Recurrent Convolutional Neural Network (RCNN) based Visual Odometry Approach for Endoscopic Capsule Robots

Turan, M., Almalioglu, Y., Araujo, H., Konukoglu, E., Sitti, M.

ArXiv e-prints, 2017 (article)

Abstract
Ingestible wireless capsule endoscopy is an emerging minimally invasive diagnostic technology for inspection of the GI tract and diagnosis of a wide range of diseases and pathologies. Medical device companies and many research groups have recently made substantial progresses in converting passive capsule endoscopes to active capsule robots, enabling more accurate, precise, and intuitive detection of the location and size of the diseased areas. Since a reliable real time pose estimation functionality is crucial for actively controlled endoscopic capsule robots, in this study, we propose a monocular visual odometry (VO) method for endoscopic capsule robot operations. Our method lies on the application of the deep Recurrent Convolutional Neural Networks (RCNNs) for the visual odometry task, where Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) are used for the feature extraction and inference of dynamics across the frames, respectively. Detailed analyses and evaluations made on a real pig stomach dataset proves that our system achieves high translational and rotational accuracies for different types of endoscopic capsule robot trajectories.

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link (url) Project Page [BibTex]


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Analytical probabilistic modeling of RBE-weighted dose for ion therapy

Wieser, H., Hennig, P., Wahl, N., Bangert, M.

Physics in Medicine and Biology (PMB), 62(23):8959-8982, 2017 (article)

pn

link (url) [BibTex]

link (url) [BibTex]


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Evaluation of the passive dynamics of compliant legs with inertia

Györfi, B.

University of Applied Science Pforzheim, Germany, 2017 (mastersthesis)

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[BibTex]

[BibTex]


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On Maximum Entropy and Inference

Gresele, L., Marsili, M.

Entropy, 19(12):article no. 642, 2017 (article)

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link (url) [BibTex]

link (url) [BibTex]


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Towards Engagement Models that Consider Individual Factors in HRI: On the Relation of Extroversion and Negative Attitude Towards Robots to Gaze and Speech During a Human-Robot Assembly Task

Ivaldi, S., Lefort, S., Peters, J., Chetouani, M., Provasi, J., Zibetti, E.

International Journal of Social Robotics, 9(1):63-86, 2017 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Non-parametric Policy Search with Limited Information Loss

van Hoof, H., Neumann, G., Peters, J.

Journal of Machine Learning Research , 18(73):1-46, 2017 (article)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Stability of Controllers for Gaussian Process Dynamics

Vinogradska, J., Bischoff, B., Nguyen-Tuong, D., Peters, J.

Journal of Machine Learning Research, 18(100):1-37, 2017 (article)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Learning Optimal Configurations for Modeling Frowning by Transcranial Electrical Stimulation

Sücker, K.

Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2017 (mastersthesis)

ei

[BibTex]

[BibTex]


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SUV-quantification of physiological lung tissue in an integrated PET/MR-system: Impact of lung density and bone tissue

Seith, F., Schmidt, H., Gatidis, S., Bezrukov, I., Schraml, C., Pfannenberg, C., la Fougère, C., Nikolaou, K., Schwenzer, N.

PLOS ONE, 12(5):1-13, 2017 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Understanding FORC using synthetic micro-structured systems with variable coupling- and coercivefield distributions

Groß, Felix

Universität Stuttgart, Stuttgart, 2017 (mastersthesis)

mms

[BibTex]


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Corrosion-protected hybrid nanoparticles

Jeong, H., Alarcón-Correa, M., Mark, A. G., Son, K., Lee, T., Fischer, P.

{Advanced Science}, 4(12), Wiley-VCH, Weinheim, 2017 (article)

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DOI [BibTex]

DOI [BibTex]


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Investigation of the Dzyaloshinskii-Moriya interaction and room temperature skyrmions in W/CoFeB/MgO thin films and microwires

Jaiswal, S., Litzius, K., Lemesh, I., Büttner, F., Finizio, S., Raabe, J., Weigand, M., Lee, K., Langer, J., Ocker, B., Jakob, G., Beach, G. S. D., Kläui, M.

{Applied Physics Letters}, 111(2), American Institute of Physics, Melville, NY, 2017 (article)

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DOI [BibTex]

DOI [BibTex]


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Ultrafast demagnetization after femtosecond laser pulses: Transfer of angular momentum from the electronic system to magnetoelastic spin-phonon modes

Fähnle, M., Tsatsoulis, T., Illg, C., Haag, M., Müller, B. Y., Zhang, L.

{Journal of Superconductivity and Novel Magnetism}, 30(5):1381-1387, Springer Science + Business Media B.V., New York, 2017 (article)

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DOI [BibTex]

DOI [BibTex]


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Magnetic behavior of single chain magnets in metal organic frameworks CPO-27-Co

Son, K., Goering, E., Hirscher, M., Oh, H.

{Journal of Nanoscience and Nanotechnology}, 17(10):7541-7546, American Scientific Publishers, Stevenson Ranch, Calif., 2017 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Switching by domain-wall automotion in asymmetric ferromagnetic rings

Mawass, M., Richter, K., Bisig, A., Reeve, R. M., Krüger, B., Weigand, M., Stoll, H., Krone, A., Kronast, F., Schütz, G., Kläui, M.

{Physical Review Applied}, 7(4), American Physical Society, College Park, Md. [u.a.], 2017 (article)

mms

DOI [BibTex]

DOI [BibTex]


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A neutral atom moving in an external magnetic field does not feel a Lorentz force

Fähnle, M.

{American Journal of Modern Physics}, 6(6):153-155, Science Publishing Group, New York, NY, 2017 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Adsorption von Wasserstoffmolekülen in nanoporösen Gerüststrukturen

Kotzur, Nadine

Universität Stuttgart, Stuttgart, 2017 (mastersthesis)

mms

[BibTex]

[BibTex]


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Temperature-dependent first-order reversal curve measurements on unusually hard magnetic low-temperature phase of MnBi

Muralidhar, S., Gräfe, J., Chen, Y., Etter, M., Gregori, G., Ener, S., Sawatzki, S., Hono, K., Gutfleisch, O., Kronmüller, H., Schütz, G., Goering, E. J.

{Physical Review B}, 95(2), American Physical Society, Woodbury, NY, 2017 (article)

mms

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Smooth and rapid microwave synthesis of MIL-53(Fe) including superparamagnetic \textlessgamma\textgreater-Fe2O3 nanoparticles

Wengert, S., Albrecht, J., Ruoß, S., Stahl, C., Schütz, G., Schäfer, R.

{Journal of Magnetism and Magnetic Materials}, 444, pages: 168-172, NH, Elsevier, Amsterdam, 2017 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Characterization and differentiation of rock varnish types from different environments by microanalytical techniques

Macholdt, D. S., Jochum, K. P., Pöhlker, C., Arangio, A., Förster, J., Stoll, B., Weis, U., Weber, B., Müller, M., Kappl, M., Shiraiwa, M., Kilcoyne, A. L. D., Weigand, M., Scholz, D., Haug, G. H., Al-Amri, A., Andreae, M. O.

{Chemical Geology}, 459, pages: 91-118, Elsevier, Amsterdam, 2017 (article)

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DOI [BibTex]

DOI [BibTex]


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Skyrmion Hall effect revealed by direct time-resolved X-ray microscopy

Litzius, K., Lemesh, I., Krüger, B., Bassirian, P., Caretta, L., Richter, K., Büttner, F., Sato, K., Tretiakov, O. A., Förster, J., Reeve, R. M., Weigand, M., Bykova, I., Stoll, H., Schütz, G., Beach, G. S. D., Kläui, M.

{Nature Physics}, 13(2):170-175, Nature Pub. Group, London, 2017 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Comment on magnonic black holes

Fähnle, M., Schütz, G.

{Journal of Magnetism and Magnetic Materials}, 444, pages: 146-146, NH, Elsevier, Amsterdam, 2017 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Cr-Substitution in Ba2In2O5 \mbox⋅ (H2O)x (x \textequals 0.16, 0.74)

Yoon, S., Son, K., Hagemann, H., Widenmeyer, M., Weidenkaff, A.

{Solid State Sciences}, 73, pages: 1-6, Elsevier Masson SAS, Paris, 2017 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Comment on half-integer quantum numbers for the total angular momentum of photons in light beams with finite lateral extensions

Fähnle, M.

{American Journal of Modern Physics}, 6(5):88-90, Science Publishing Group, New York, NY, 2017 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Advanced magneto-optical Kerr effect measurements of superconductors at low temperatures

Stahl, C., Gräfe, J., Ruoß, S., Zahn, P., Bayer, J., Simmendinger, J., Schütz, G., Albrecht, J.

{AIP Advances}, 7(10), 2017 (article)

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DOI [BibTex]

DOI [BibTex]


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Unifying ultrafast demagnetization and intrinsic Gilbert damping in Co/Ni bilayers with electronic relaxation near the Fermi surface

Zhang, W., He, W., Zhang, X.-Q., Cheng, Z.-H., Teng, J., Fähnle, M.

{Physical Review B}, 96(22), American Physical Society, Woodbury, NY, 2017 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Influence of the skin barrier on the penetration of topically-applied dexamethasone probed by soft X-ray spectromicroscopy

Yamamoto, K., Klossek, A., Flesch, R., Rancan, F., Weigand, M., Bykova, I., Bechtel, M., Ahlberg, S., Vogt, A., Blume-Peytavi, U., Schrade, P., Bachmann, S., Hedtrich, S., Schäfer-Korting, M., Rühl, E.

{European Journal of Pharmaceutics and Biopharmaceutics}, 118, pages: 30-37, Elsevier, Amsterdam, 2017 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Capture of heavy hydrogen isotopes in a metal-organic framework with active Cu(I) sites

Weinrauch, I., Savchenko, I., Denysenko, D., Souliou, S. M., Kim, H., Le Tacon, M., Daemen, L. L., Cheng, Y., Mavrandonakis, A., Ramirez-Cuesta, A. J., Volkmer, D., Schütz, G., Hirscher, M., Heine, T.

{Nature Communications}, 8, Nature Publishing Group, London, 2017 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Multiscale simulations of topological transformations in magnetic-skyrmion spin structures

De Lucia, A., Litzius, K., Krüger, B., Tretiakov, O. A., Kläui, M.

{Physical Review B}, 96(2), American Physical Society, Woodbury, NY, 2017 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Unexpectedly marginal effect of electronic correlations on ultrafast demagnetization after femtosecond laser-pulse excitation

Weng, W., Huang, Haonan, Briones Paz, J. Z., Teeny, N., Müller, B. Y., Haag, M., Kuhn, T., Fähnle, M.

{Physical Review B}, 95(22), American Physical Society, Woodbury, NY, 2017 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Black manganese-rich crusts on a Gothic cathedral

Macholdt, D. S., Herrmann, S., Jochum, K. P., Kilcoyne, A. L. D., Laubscher, T., Pfisterer, H. K., Pöhlker, C., Schwager, B., Weber, B., Weigand, M., Domke, K. F., Andreae, M. O.

{Atmospheric Environment}, 171, pages: 205-220, Elsevier, Amsterdam [u.a.], 2017 (article)

mms

DOI [BibTex]

DOI [BibTex]