Despite the breakthroughs in accuracy and speed of single image super-resolution using
faster and deeper convolutional neural networks, one central problem remains largely …

Object proposals have contributed significantly to recent advances in object understanding
in images. Inspired by the success of this approach, we introduce Deep Action Proposals …

Recent advances in AutoML have led to automated tools that can compete with machine
learning experts on supervised learning tasks. However, current AutoML tools do not yet …

To achieve peak predictive performance, hyperparameter optimization (HPO) is a crucial
component of machine learning and its applications. Over the last years, the number of …

Abstract The ChaLearn AutoML Challenge (The authors are in alphabetical order of last
name, except the first author who did most of the writing and the second author who …

Tracking congestion throughout the network road is a critical component of Intelligent
transportation network management systems. Understanding how the traffic flows and short …

Automatic Offline Handwritten Signature Verification has been researched over the last few
decades from several perspectives, using insights from graphology, computer vision, signal …

In their most aggressive form, the mortality rate of gliomas is high. Accurate segmentation is
important for surgery and treatment planning, as well as for follow-up evaluation. In this …

The EEG of epileptic patients often contains sharp waveforms called" spikes", occurring
between seizures. Detecting such spikes is crucial for diagnosing epilepsy. In this paper, we …

In the context of future urban automated driving many important problems remain unsolved.
A critical one is the analysis and prediction of pedestrian movements around urban roads …