13 papers:
ICDAR-2013-SaidaniEB #identification #word- Identification of Machine-Printed and Handwritten Words in Arabic and Latin Scripts (AS, AKE, AB), pp. 798–802.
CHI-2012-OganWBRCLC #case study #collaboration #design #recommendation- Collaboration in cognitive tutor use in latin America: field study and design recommendations (AO, EW, RSJdB, GRM, MJC, TL, AMJBdC), pp. 1381–1390.
- ICDAR-2009-BenjelilKMA #identification
- Arabic and Latin Script Identification in Printed and Handwritten Types Based on Steerable Pyramid Features (MB, SK, RM, AMA), pp. 591–595.
- ICDAR-2009-KessentiniPB #multi #recognition
- A Multi-Lingual Recognition System for Arabic and Latin Handwriting (YK, TP, ABH), pp. 1196–1200.
IDGD-2009-Rodriguez #community- Affordable Wireless Connectivity Linking Poor Latin American Communities Binding Their Schools by Sharing ICT Training for “Maestros” of Primary Schools (COR), pp. 404–412.
SIGMOD-2008-OlstonRSKT- Pig latin: a not-so-foreign language for data processing (CO, BR, US, RK, AT), pp. 1099–1110.
ICPR-2008-ChandraS #using- A method for removing cyclic artefacts in discrete tomography using latin squares (SC, IDS), pp. 1–4.
- ICDAR-2007-JlaielKAM #difference
- Three decision levels strategy for Arabic and Latin texts differentiation in printed and handwritten natures (MBJ, SK, AMA, RM), pp. 1103–1107.
- ICDAR-2007-LuLT #categorisation #identification
- Identification of Latin-Based Languages through Character Stroke Categorization (SJL, LL, CLT), pp. 352–356.
- ICDAR-2005-VajdaB #recognition #word
- Structural Information Implant in a Context Based Segmentation-Free HMM Handwritten Word Recognition System for Latin and Bangla Script (SV, AB), pp. 1126–1130.
- ICDAR-1999-LaaksonenAOK #adaptation #online #recognition
- Dynamically Expanding Context as Committee Adaptation Method in On-Line Recognition of Handwritten Latin Characters (JL, MA, EO, JK), pp. 796–799.
- ICDAR-v2-1995-Romeo-PakkerML #approach #segmentation
- A new approach for Latin/Arabic character segmentation (KRP, HM, YL), pp. 874–877.
- ICDAR-v2-1995-ZiinoAS #machine learning #recognition #using
- Recognition of hand printed Latin characters using machine learning (DZ, AA, CS), pp. 1098–1102.
