People detection is an important task for a wide range of applications in computer vision. State-of-the-art methods learn appearance based models requiring tedious collection and ...
Leonid Pishchulin, Christian Wojek, Arjun Jain, Th...
Insufficient training data is one of the major problems in neural network learning, because it leads to poor learning performance. In order to enhance an intelligent learning proc...
In this paper we present a novel approach for patternconstrained test case generation. The generation of test cases with known characteristics is usually a non-trivial task. In co...
Traditional deployments of wireless sensor networks (WSNs) rely on static basestations to collect data. For applications with highly spatio-temporal and dynamic data generation, su...
In this paper we introduce a modular, highly flexible, opensource environment for data generation. Using an existing graphical data flow tool, the user can combine various types...
Fault-based testing is often advocated to overcome limitations of other testing approaches; however it is also recognized as being expensive. On the other hand, evolutionary algor...
Computationally complex and data intensive atomic scale biomolecular simulation is enabled via Processing in Network Storage (PINS): a novel distributed system framework to overco...
Paul Brenner, Justin M. Wozniak, Douglas Thain, Aa...