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» Learning Mid-Level Features For Recognition
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ICDAR
2009
IEEE
14 years 2 months ago
Statistical Modeling and Learning for Recognition-Based Handwritten Numeral String Segmentation
This paper proposes a recognition based approach to handwritten numeral string segmentation. We consider two classes: numeral strings segmented correctly or not. The feature vecto...
Yanjie Wang, Xiabi Liu, Yunde Jia
ICIP
2009
IEEE
14 years 8 months ago
Using Sparse Regression To Learn Effective Projections For Face Recognition
We explore sparse regression for effective feature selection and classification in face identity and expression recognition. We argue that sparse regression in pixel space is inap...
ECAI
2008
Springer
13 years 9 months ago
Learning to Select Object Recognition Methods for Autonomous Mobile Robots
Selecting which algorithms should be used by a mobile robot computer vision system is a decision that is usually made a priori by the system developer, based on past experience and...
Reinaldo A. C. Bianchi, Arnau Ramisa, Ramon L&oacu...
BMVC
1998
13 years 9 months ago
ORASSYLL: Object Recognition with Autonomously Learned and Sparse Symbolic Representations Based on Local Line Detectors
We introduce an object recognition system in which objects are represented as a sparse and spatially organized set of local (bent) line segments. The line segments correspond to b...
Norbert Krüger, Niklas Lüdtke
ACL
2008
13 years 9 months ago
Word Clustering and Word Selection Based Feature Reduction for MaxEnt Based Hindi NER
Statistical machine learning methods are employed to train a Named Entity Recognizer from annotated data. Methods like Maximum Entropy and Conditional Random Fields make use of fe...
Sujan Kumar Saha, Pabitra Mitra, Sudeshna Sarkar