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» A Generalization of Automatic Sequences
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ECAI
2004
Springer
14 years 2 months ago
Learning Complex and Sparse Events in Long Sequences
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
Marco Botta, Ugo Galassi, Attilio Giordana
GECCO
2003
Springer
148views Optimization» more  GECCO 2003»
14 years 2 months ago
Structural and Functional Sequence Test of Dynamic and State-Based Software with Evolutionary Algorithms
Evolutionary Testing (ET) has been shown to be very successful for testing real world applications [10]. The original ET approach focusesonsearching for a high coverage of the test...
André Baresel, Hartmut Pohlheim, Sadegh Sad...
ECAI
2000
Springer
14 years 1 months ago
Activity Recognition from Video Sequences using Declarative Models
Abstract. We propose here a new approach for video sequence interpretation based on declarative models of activities. The aim of the video sequence interpretation is to recognize i...
Nathanaël Rota, Monique Thonnat
VLSISP
1998
111views more  VLSISP 1998»
13 years 8 months ago
Quantitative Analysis of MR Brain Image Sequences by Adaptive Self-Organizing Finite Mixtures
This paper presents an adaptive structure self-organizing finite mixture network for quantification of magnetic resonance (MR) brain image sequences. We present justification fo...
Yue Wang, Tülay Adali, Chi-Ming Lau, Sun-Yuan...
CSCW
2006
ACM
14 years 2 months ago
Improving network efficiency in real-time groupware with general message compression
Groupware communicates by sending messages across the network, and groupware programmers use a variety of formats for these messages, such as XML, plain text, or serialized object...
Carl Gutwin, Christopher Fedak, Mark Watson, Jeff ...