We are developing a system to extract geodetic, textured CAD models from thousands of initially uncontrolled, close-range ground and aerial images of urban scenes. Here we describ...
Current methods for learning visual categories work well when a large amount of labeled data is available, but can run into severe difficulties when the number of labeled examples...
We present a physically-based multiphase model for simulating water and air bubbles with Smoothed Particle Hydrodynamics (SPH). Since the high density ratio of air and water is pr...
Markus Ihmsen, Julian Bader, Gizem Akinci, Matthia...
Background: Since experimental determination of protein folding pathways remains difficult, computational techniques are often used to simulate protein folding. Most current techn...
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...