Travelled to:
1 × Canada
1 × China
1 × Germany
1 × India
1 × Korea
1 × Spain
1 × Turkey
1 × USA
2 × United Kingdom
Collaborated with:
S.Marinai E.Marino F.Cesarini M.Gori B.Miotti E.Francesconi S.Baldi J.Sheng P.Frasconi A.Vullo L.Sarti M.Lastri
Talks about:
document (9) retriev (4) tree (4) recognit (3) imag (3) use (3) understand (2) mathemat (2) approach (2) cluster (2)
Person: Giovanni Soda
DBLP: Soda:Giovanni
Contributed to:
Wrote 17 papers:
- ICDAR-2011-MarinaiMS
- Conversion of PDF Books in ePub Format (SM, EM, GS), pp. 478–482.
- ICDAR-2011-MarinaiMS11a #distance #retrieval #using
- Using Earth Mover’s Distance in the Bag-of-Visual-Words Model for Mathematical Symbol Retrieval (SM, BM, GS), pp. 1309–1313.
- DocEng-2010-MarinaiMS #documentation #recognition
- Table of contents recognition for converting PDF documents in e-book formats (SM, EM, GS), pp. 73–76.
- ICPR-2010-MarinaiMS #clustering #identification #recognition
- Bag of Characters and SOM Clustering for Script Recognition and Writer Identification (SM, BM, GS), pp. 2182–2185.
- ICDAR-2009-MarinaiMS #clustering #order #using
- Mathematical Symbol Indexing Using Topologically Ordered Clusters of Shape Contexts (SM, BM, GS), pp. 1041–1045.
- ECDL-2007-MarinaiMS #documentation #image #library #retrieval
- Exploring Digital Libraries with Document Image Retrieval (SM, EM, GS), pp. 368–379.
- ICDAR-2005-MarinaiMS #documentation #image #layout #reduction #retrieval
- Layout based document image retrieval by means of XY tree reduction (SM, EM, GS), pp. 432–436.
- ICDAR-2003-BaldiMS #classification #set #using
- Using tree-grammars for training set expansion in page classification (SB, SM, GS), pp. 829–833.
- ICDAR-2003-MarinaiMS #documentation #retrieval #word
- Indexing and retrieval of words in old documents (SM, EM, GS), pp. 223–227.
- ICPR-v3-2002-CesariMSS #documentation #image
- Trainable Table Location in Document Images (FC, SM, LS, GS), pp. 236–240.
- ICDAR-2001-CesariniLMS #classification #documentation #encoding
- Encoding of Modified X-Y Trees for Document Classification (FC, ML, SM, GS), pp. 1131–1136.
- ICDAR-1999-CesariniFGS #approach #comprehension #documentation #multi
- A Two Level Knowledge Approach for Understanding Documents of a Multi-Class Domain (FC, EF, MG, GS), pp. 135–138.
- ICDAR-1999-CesariniGMS #documentation #representation #segmentation
- Structured Document Segmentation and Representation by the Modified X-Y tree (FC, MG, SM, GS), pp. 563–566.
- ICDAR-1997-CesariniFGMSS #architecture #recognition
- A Neural-Based Architecture for Spot-Noisy Logo Recognition (FC, EF, MG, SM, JS, GS), pp. 175–179.
- ICDAR-1997-CesariniFGMSS97a #comprehension
- Rectangle Labelling for an Invoice Understanding System (FC, EF, MG, SM, JS, GS), pp. 324–330.
- ICDAR-v2-1995-CesariniGMS
- A system for data extraction from forms of known class (FC, MG, SM, GS), pp. 1136–1140.
- JCDL-2001-FrasconiSV #approach #categorisation #documentation #hybrid #multi #naive bayes
- Text categorization for multi-page documents: a hybrid naive Bayes HMM approach (PF, GS, AV), pp. 11–20.