A5012844162- Homotopy and Cohomology in Algebraic Topology
- Algebraic structures and combinatorial models
- Advanced Combinatorial Mathematics
- Advanced Topics in Algebra
- Algebraic Geometry and Number Theory
- Advanced Vision and Imaging
- Neural Networks and Applications
- Visual perception and processing mechanisms
- Geometric and Algebraic Topology
- Advanced Image and Video Retrieval Techniques
- Control Systems and Identification
- Health and Medical Studies
- Image and Signal Denoising Methods
- Climate Change and Geoengineering
- Robotics and Sensor-Based Localization
- Medical Image Segmentation Techniques
- Psychosomatic Disorders and Their Treatments
- Neurobiology and Insect Physiology Research
- 3D Surveying and Cultural Heritage
- Space Science and Extraterrestrial Life
- Visual Attention and Saliency Detection
- Medical Practices and Rehabilitation
- Medical Imaging Techniques and Applications
- Advanced X-ray and CT Imaging
- Robotic Path Planning Algorithms
Western University
2014-2025
HTWG Hochschule Konstanz - Technik, Wirtschaft und Gestaltung
2014-2024
University of Göttingen
2023
Stuttgart Media University
2013-2019
Heinrich Heine University Düsseldorf
2000-2016
Düsseldorf University Hospital
2014-2016
Klinik und Poliklinik für Frauenheilkunde und Geburtshilfe
2016
Schölly (Germany)
2016
Klinik für Frauenheilkunde
2016
Ludwig-Maximilians-Universität München
2016
The theory of general relativity describes macroscopic phenomena driven by the influence gravity while quantum mechanics brilliantly accounts for microscopic effects.Despite their tremendous individual success, a complete unification fundamental interactions is missing and remains one most challenging important quests in modern theoretical physics.The STE-QUEST satellite mission, proposed as medium-size mission within Cosmic Vision program European Space Agency (ESA), aims testing with high...
In recent years, kernel principal component analysis (KPCA) has been suggested for various image processing tasks requiring an model such as, e.g., denoising or compression. The original form of KPCA, however, can be only applied to strongly restricted classes due the limited number training examples that processed. We therefore propose a new iterative method performing Hebbian algorithm, which iteratively estimates components with linear order memory complexity. our experiments, we compute...
The human visual system is foveated, that is, outside the central field resolution and acuity drop rapidly. Nonetheless much of a scene perceived after only few saccadic eye movements, suggesting an effective strategy for selecting saccade targets. It has been known some time local image structure at targets influences selection process. However, question what most relevant features are still under debate. Here we show center-surround patterns emerge as optimal solution predicting from their...
Volterra and Wiener series are perhaps the best-understood nonlinear system representations in signal processing. Although both approaches have enjoyed a certain popularity past, their application has been limited to rather low-dimensional weakly systems due exponential growth of number terms that be estimated. We show can represented implicitly as elements reproducing kernel Hilbert space by using polynomial kernels. The estimation complexity implicit representation is linear input...
Classification of plants according to their echoes is an elementary component bat behavior that plays important role in spatial orientation and food acquisition. Vegetation are, however, highly complex stochastic signals: from acoustical point view, a plant can be thought as three-dimensional array leaves reflecting the emitted call. The received echo therefore superposition many reflections. In this work we suggest classification these might not such troublesome routine for bats formerly...
Echolocating bats use the echoes from their echolocation calls to perceive surroundings. The ability these continuously emitted calls, whose main function is not communication, for recognition of individual conspecifics might facilitate many social behaviours observed in bats. Several studies individual-specific information found some evidence its existence but did quantify or explain it. We used a direct paradigm show that greater mouse-eared (Myotis myotis) can easily discriminate between...
Tangential neurons in the fly brain are sensitive to typical optic flow patterns generated during egomotion. In this study, we examine whether a simplified linear model based on organization principles tangential can be used estimate egomotion from flow. We present theory for construction of an estimator consisting combination vectors that incorporates prior knowledge about distance distribution environment and noise statistics sensor. The is tested gantry carrying omnidirectional vision...
A critical step on the way to understanding a sensory system is analysis of input it receives. In this work we examine statistics natural complex echoes, focusing vegetation echoes. Vegetation echoes constitute major part world more than 800 species echolocating bats and play an important role in several their daily tasks. Our statistical based large collection plant acquired by biomimetic sonar system. We explore relation between physical (the structure plant) characteristics its echo....
Let <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="upper X"> <mml:semantics> <mml:mi>X</mml:mi> <mml:annotation encoding="application/x-tex">X</mml:annotation> </mml:semantics> </mml:math> </inline-formula> be a “nice” space with an action of torus T"> <mml:mi>T</mml:mi> encoding="application/x-tex">T</mml:annotation> </inline-formula>. We consider the Atiyah–Bredon sequence equivariant cohomology modules arising from filtration...
In this paper we present a method using deep learning to compute parametrizations for B-spline curve approximation. Existing methods consider the computation of parametric values and knot vector as separate problems. We propose train interdependent neural networks predict knots. show that it is possible include approximation directly into network architecture. The resulting yield tight approximations are able outperform state-of-the-art methods.