Search Results - "Thollard, F."

Probabilistic finite-state machines - part I by Vidal, E., Thollard, F., de la Higuera, C., Casacuberta, F., Carrasco, R.C.

“…Probabilistic finite-state machines are used today in a variety of areas in pattern recognition, or in fields to which pattern recognition is linked:…”
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Probabilistic finite-state machines - part II by Vidal, E., Thollard, F., de la Higuera, C., Casacuberta, F., Carrasco, R.C.

“…Probabilistic finite-state machines are used today in a variety of areas in pattern recognition or in fields to which pattern recognition is linked. In part I…”
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pygeodyn 1.1.0: a Python package for geomagnetic data assimilation by Huder, Loïc, Gillet, Nicolas, Thollard, Franck

“…The pygeodyn package is a sequential geomagnetic data assimilation tool written in Python. It gives access to the core surface dynamics, controlled by…”
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Probabilistic finite-state machines--part II by Vidal, Enrique, Thollard, Frank, de la Higuera, Colin, Casacuberta, Francisco, Carrasco, Rafael C

“…Probabilistic finite-state machines are used today in a variety of areas in pattern recognition or in fields to which pattern recognition is linked. In Part I…”
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From Text Detection in Videos to Person Identification by Poignant, J., Besacier, L., Quenot, G., Thollard, F.

“…We present in this article a video OCR system that detects and recognizes overlaid texts in video as well as its application to person identification in video…”
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Text detection and recognition for person identification in videos by Poignant, J., Thollard, F., Quenot, G., Besacier, L.

“…This article presents a demo of person search in audiovisual broadcast using only the text available in a video and in resources external to the video. We also…”
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Integrating Structure in the Probabilistic Model for Information Retrieval by Gery, Mathias, Largeron, Christine, Thollard, Franck

“…In databases or in the World Wide Web, many documents are in a structured format (e.g. XML). We propose in this article to extend the classical IR…”
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Using the H-Divergence to Prune Probabilistic Automata by Bernard, M., Jeudy, B., Peyrache, Jean-Philippe, Sebban, M., Thollard, F.

“…A problem usually encountered in probabilistic automata learning is the difficulty to deal with large training samples and/or wide alphabets. This is partially…”
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