The lexical identification shift is used as a measure of speech processing in the phoneme identification task (W. F. Ganong, 1980). Interactive (bottom-up and top-down) models of word recognition account for the shift by claiming that lexical knowledge feeds back to a prelexical level and aids speech processing. Autonomous models (bottom-up only) maintain that the shift arises by other means an...

The speed of visual processing is central to our understanding of face perception. Yet the extent to which early visual processing influences later processing in distributed face processing networks, and the top-down modulation of such bottom-up effects, remains unclear. We used simultaneous EEG-fMRI to investigate cortical activity that showed unique covariation with ERP components of face pro...

Stemmers have many applications in natural language processing and some fields such as information retrieval. Many algorithms have been proposed for stemming. In this paper, we propose a new algorithm for Persian language. Our algorithm is a bottom up algorithm that is capable to reorganize without changing the implementation. Our experiments show that the proposed algorithm has a suitable resu...

Resource usage models are important asset to analyze and ensure the adequate usage of the system platform resources such as processors and memory elements. In this paper, we present how to construct resource usage models using actual execution information of a large software-intensive system. We have constructed this type of models for an MRI system (a representative large software-intensive sy...

In this paper, we are interested with the groundtruthing problem for performance evaluation of symbol recognition & spotting systems. We propose a complete framework based on user interaction scheme through a tactile device, exploiting image processing components to achieve groundtruthing of real-life documents in an semi-automatic way. It is based on a top-down matching algorithm, to make the ...

Multidimensional data is systematically analysed at multiple granularities by applying aggregate and disaggregate operators (e.g., by the use of OLAP tools). For instance, in a supermarket we may want to predict sales of tomatoes for next week, but we may also be interested in predicting sales for all vegetables (higher up in the product hierarchy) for next Friday (lower down in the time dimens...

The hypothesis is tested whether the P1 of the event-related potential (ERP) component behaves like an evoked, traveling alpha wave. This hypothesis is based on different kinds of evidence showing e.g. that-after undergoing phase reorganization-frequencies in the broad alpha range become synchronized (aligned) in absolute phase and contribute significantly to the generation of the P1. We invest...

in Proc. IEEE Int’l Conf. on Image Processing 2001, Thessaloniki, Greece To track multiple objects, top-down (model-based methods) and bottom-up (multi-layer analysis) methods have been proposed separately. In this paper, a hierarchical MRF model is proposed to integrate these two trends into a MAP framework for tracking non-rigid objects such as human hands or faces. Parametric models of color...

We humans are easily able to instantaneously detect the regions in a visual scene that are most likely to contain something of interest. Exploiting this pre-selection mechanism called visual attention for image and video processing systems would make them more sophisticated and therefore more useful. This paper briefly describes various computational models of human visual attention and their d...

We show how to use a sampling method to find sparsely clad people in static images. People are modeled as an assembly of nine cylindrical segments. Segments are found using an EM algorithm, and then assembled into hypotheses incrementally, using a learned likelihood model. Each assembly step passes on a set of samples of its likelihood to the next; this yields effective pruning of the space of ...