Understanding the meaning of a word in its current context is one of the big challenges when searching for information. STICS is a new kind of semantic search engine that not only searches for words, but for meaning: it understands concepts and categories.
3D printing gives new opportunities in object replication. We built a computational model with which we will compare perceived properties of different materials and choose the one best suited for printing the desired object.
Computational aspects of routing and pricing problems share more similarities than one would imagine. Theoreticians as well as practitioners can benefit from our transfer of routing problem knowledge to pricing problems.
Comparing genomes of parents and children separates inherited genetic variants from new mutations. The rate of novo mutations is an important parameter in models of human evolution.
New algorithms facilitate complex video processing such as automatic dynamic background inpainting. New machine learning algorithms make possible the removal of compression artifacts from images and videos.
With the work of Anna and Markus Rohrbach the automatic generation of subtitles or the automatic movie description for the blind becomes a realistic objective.
The 3D reconstruction of detailed models of persons in general apparel is, until now, possible in indoor sudios with controlled environment only. With new algorithms this seems it could succeed even in arbitrarily complex outdoor scenes with only a few camera.
Instead of using a large variety of classifier types, it is possible to obtain best results in shortest time by precisely applying the sliding windows technique.
Using a new design model (3D object class detector) not only the efficient detection of objects and their 2D position in a picture is possible, but also their relative 3D position and view point estimation.
We developed a novel mathematical approach that allows streak and time lines to be described using ordinary differential equations therewith overcoming the drawbacks of former complex algorithms.
Olga Kalinina combines genomic-, modeling-, and biophysics-based methods to assess the mutations observed in given sequences of viral proteins and infer their potential influence on the function of the protein. This enables suggestions for drug treatment of viral diseases.
We could improve the bounds of numerical steps needed to find an exact solution for polynomial systems by multiple orders of magnitude. Given present knowledge, they are nearly optimal.