Learning Search Strategies from Human Demonstrations
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In this paper we aim to explore what is the most appropriate number of data samples needed when measuring the temporal correspondence between a chosen set of video and audio cues in a given audio-visual sequence. Presently the optimal model that connects s ...
A multimodal probabilistic framework is proposed for the problem of finding the active speaker in a video sequence. We localize the current speaker's mouth in the image by using the video and the audio channels together. We propose a novel visual feature t ...
This paper addresses qualitative and quantitative diversity and specialization issues in the framework of selforganizing, distributed, artificial systems. Both diversity and specialization are obtained via distributed learning from initially homogeneous sw ...
Based on experiences in the design and construction of interactive resource reallocation systems, the authors argue about the advisability of interactive visualization as a means to increase the effectiveness of an intelligent system and present a generic ...
This paper proposes the use of Gaussian Mixture Models to estimate conditional probability density functions. A conditional Gaussian Mixture Model has been compared to the geostatistical method of Sequential Gaussian Simulations. The data set used is a par ...
In this paper, we present a way to track multiple maneuvering targets with varying time-frequency signatures. A particle filter is used to track targets that have constant speeds with changing heading directions. The target motion dynamics help the particl ...
This paper develops a unified approach to the analysis and design of adaptive filters with error nonlinearities. In particular, the paper performs stability and steady-state analysis of this class of filters under weaker conditions than what is usually enc ...
This paper addresses qualitative and quantitative diversity and specialization issues in the frame- work of self-organizing, distributed, artificial systems. Both diversity and specialization are obtained via distributed learning from initially homogeneous ...
We provide an overview of the evolutionary approach to the emergence of artificial intelligence in embodied behavioral agents. This approach, also known as Evolutionary Robotics, builds and capitalizes upon the interactions between the embodied agent and i ...
