Person: Volkmar Frinken

DBLP: Frinken:Volkmar

Contributed to:

2014

2013

2012

2011

2011

2010

2009

Wrote 11 papers:

ICPR-2014-FrinkenIIFU #recognition

Improving Point of View Scene Recognition by Considering Textual Data (VF, YI, RI, KF, SU), pp. 2966–2971.

ICPR-2014-InaiPFFU #privacy

Selective Concealment of Characters for Privacy Protection (KI, MP, VF, YF, SU), pp. 333–338.

ICDAR-2013-FischerFBS #keyword #modelling

Improving HMM-Based Keyword Spotting with Character Language Models (AF, VF, HB, CYS), pp. 506–510.

ICPR-2012-FrinkenZBBFB #memory management #modelling #network #recognition

Long-short term memory neural networks language modeling for handwriting recognition (VF, FZM, SEB, MJCB, AF, HB), pp. 701–704.

ICDAR-2011-FischerIFB #documentation

HMM-Based Alignment of Inaccurate Transcriptions for Historical Documents (AF, EI, VF, HB), pp. 53–57.

ICDAR-2011-FrinkenFBF #recognition #word

Co-training for Handwritten Word Recognition (VF, AF, HB, AF), pp. 314–318.

ICDAR-2011-IndermuhleFFB #documentation #keyword #network #online #using

Keyword Spotting in Online Handwritten Documents Containing Text and Non-text Using BLSTM Neural Networks (EI, VF, AF, HB), pp. 73–77.

ICDAR-2011-JainFJM #documentation #network #retrieval #word

BLSTM Neural Network Based Word Retrieval for Hindi Documents (RJ, VF, CVJ, RM), pp. 83–87.

SAC-2011-FrinkenFB #keyword #self

Improving handwritten keyword spotting with self-training (VF, AF, HB), pp. 840–845.

ICPR-2010-FischerKFB #documentation #modelling #using #word

HMM-based Word Spotting in Handwritten Documents Using Subword Models (AF, AK, VF, HB), pp. 3416–3419.

ICDAR-2009-FrinkenB #learning #network #recognition #word

Evaluating Retraining Rules for Semi-Supervised Learning in Neural Network Based Cursive Word Recognition (VF, HB), pp. 31–35.