Sentence examples for action representations from inspiring English sources

We use a set of hierarchically arranged recurrent networks for the unsupervised learning of action representations with increasingly large spatiotemporal receptive fields.

For example, Kim and Mooney (2012) describe methods of using sentences paired with graph-based descriptions of actions and contexts to hypothesize PCFG rules for parsing NL instructions into action representations, while learning rule probabilities with the inside-outside algorithm.

However, due to the presence of background clutter, partial occlusion, varying viewpoints, and camera movement, it is still a challenging task to obtain discriminative action representations from realistic videos.

Several researchers have mistakenly attempted to simplify the MTC by eliminating the white-knight declobbering clause from it; and others have used Chapman's results to conjecture that partial-order planning will not scale up to more expressive action representations.

Utilizing a cognitive-based data reduction method and a hybrid "network upon networks" architecture, we extract human action representations which are robust against spatial and temporal interferences and adaptive to variations in both action speed and duration.

Third, many of our models were of animals, which do not have clearly associated action representations.

The language provides an expressive action representation which captures the procedural complexities of practical control programs, yet can still be projected by a search-based planner.

The system provides a unified approach since the planner and the controller share identical data structures and algorithms for interpreting a shared action representation.

This paper aims to obtain effective and compact action representation with length-variable edge trajectory (LV-ET) and spatio-temporal motion skeleton (STMS).

According to these premises, in this paper we present an approach to action representation that is based on a "conceptual" level of representation, acting as an intermediate level between symbols and data coming from sensors.

A novel visuomotor priming task was designed to pit true imitative compatibility, due to human action representation against more general stimulus response compatibility that has confounded previous belief experiments.