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125
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EMNLP
2006
15 years 4 months ago
A Hybrid Markov/Semi-Markov Conditional Random Field for Sequence Segmentation
Markov order-1 conditional random fields (CRFs) and semi-Markov CRFs are two popular models for sequence segmentation and labeling. Both models have advantages in terms of the typ...
Galen Andrew
66
Voted
ICPR
2008
IEEE
16 years 3 months ago
Image objects and multi-scale features for annotation detection
This paper investigates several issues in the problem of detecting handwritten markings, or annotations, on printed documents. One issue is to define the appropriate units over wh...
Eric Saund, Jindong Chen, Yizhou Wang
CORR
2010
Springer
137views Education» more  CORR 2010»
14 years 12 months ago
Seamless Flow Migration on Smartphones without Network Support
This paper addresses the following question: Is it possible to migrate TCP/IP flows between different networks on modern mobile devices, without infrastructure support or protocol...
Ahmad Rahmati, Clayton Shepard, Chad Tossell, Ange...
109
Voted
ICPR
2004
IEEE
16 years 3 months ago
Object Recognition Using Composed Receptive Field Histograms of Higher Dimensionality
Recent work has shown that effective methods for recognising objects or spatio-temporal events can be constructed based on receptive field responses summarised into histograms or ...
Oskar Linde, Tony Lindeberg
ICML
2004
IEEE
16 years 3 months ago
Training conditional random fields via gradient tree boosting
Conditional Random Fields (CRFs; Lafferty, McCallum, & Pereira, 2001) provide a flexible and powerful model for learning to assign labels to elements of sequences in such appl...
Thomas G. Dietterich, Adam Ashenfelter, Yaroslav B...