A human-like learning control for digital human models in a physics-based virtual environment

The aim of this paper is to develop a deep learning based formation control strategy for the multi-agent systems by using the backpropagation algorithm.. Specifically, the deep

Table 2 gives SROCC mean values computed between predicted scores from NR-IQA schemes from which some extracted features are used to design LEVIQI and MOS val- ues for the

The challenges for implementing assistive robots are the same at all levels of planning and action execution: 1) How can a robot show legible behavior? It has to make its

Applying this approach from reduced preprocessed feature vectors on the Microsoft Research Cambridge-12 (MSRC-12) Kinect gesture dataset outperforms the state-of-the-art results with

This chapter lays the foundation for the extensions required for human- control of semi-autonomous vehicles, the ultimate goal being a protocol that maintains the efficiency of a

It uses augmented reality and head-tracking to overlay a representation of an active brain on top of the user’s head, seen in a semi-reflective screen (see Figure 4, left). This

Background and Objectives: This paper presents the results of a Machine- Learning based Model Order Reduction (MOR) method applied to a complex 3D Finite Element (FE)

When the relative position of the arm and the camera respects an anthropomorphic relation, the absence of significant difference in the delimitation of corporal space between