12 papers:
SIGIR-2015-BadacheB #quality #social- A Priori Relevance Based On Quality and Diversity Of Social Signals (IB, MB), pp. 731–734.
CHI-2010-AppertB #detection #gesture #recognition- Scale detection for a priori gesture recognition (CA, OB), pp. 879–882.
ICDAR-2009-EynardE #documentation #recognition #word- Italic or Roman: Word Style Recognition without A Priori Knowledge for Old Printed Documents (LE, HE), pp. 823–827.
KDD-2007-MoserGE #analysis #clustering #specification- Joint cluster analysis of attribute and relationship data withouta-priori specification of the number of clusters (FM, RG, ME), pp. 510–519.
PPDP-2006-AlbertiGLCMM #abduction #framework #verification #web #web service- An abductive framework for a-priori verification of web services (MA, MG, EL, FC, PM, MM), pp. 39–50.
- ICDAR-2003-FeldbachT #documentation #segmentation #semantics #word
- Word Segmentation of Handwritten Dates in Historical Documents by Combining Semantic A-Priori-Knowledge with Local Features (MF, KDT), pp. 333–337.
DATE-2001-WormLW #architecture #design #performance #power management- Design of low-power high-speed maximum a priori decoder architectures (AW, HL, NW), pp. 258–267.
- ICDAR-2001-GrandidierSGS #markov #modelling #power of
- An a priori Indicator of the Discrimination Power of Discrete Hidden Markov Models (FG, RS, MG, CYS), pp. 350–355.
ICML-2001-LatinneSD #classification #multi #problem- Adjusting the Outputs of a Classifier to New a Priori Probabilities May Significantly Improve Classification Accuracy: Evidence from a multi-class problem in remote sensing (PL, MS, CD), pp. 298–305.
ICPR-v1-2000-WangL- Guiding Ziplock Snakes with a priori Information (JW, XL), pp. 1614–1617.
- ICPR-1996-Lemaire #nondeterminism #recognition
- Use of a priori descriptions in a high-level language and management of the uncertainty in a scene recognition system (JL), pp. 560–564.
- ICDAR-v1-1995-MurshedBS #approach #verification
- Off-line signature verification, without a priori knowledge of class /spl omega//sub 2/. A new approach (NAM, FB, RS), pp. 191–196.
