The most commonly used learning algorithm for restricted Boltzmann machines is contrastive divergence which starts a Markov chain at a data point and runs the chain for only a few...
Abstract. In this paper, we present a fully automatic approach to multiple human detection and tracking in high density crowds in the presence of extreme occlusion. Human detection...
In this paper, we present a real-time 3D pointing gesture recognition algorithm for natural human-robot interaction (HRI). The recognition errors in previous pointing gesture reco...
— An important milestone for building affordable robots that can become widely popular is to address robustly the Simultaneous Localization and Mapping (SLAM) problem with inexpe...
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...