Consiglio Nazionale delle Ricerche

Tipo di prodottoContributo in volume
TitoloSemi-automatic semantic tagging of 3D images from pancreas cells
Anno di pubblicazione2007
Formato-
Tipologia di contributo in volumeCapitolo
Autore/iLittle S.; Salvetti O.; Perner P.
Affiliazioni autoriInstitute of Computer Vision and Applied Computer Sciences (IBaI), Leipzig, Germany; CNR-ISTI, Pisa, Italy; Institute of Computer Vision and Applied Computer Sciences (IBaI), Leipzig, Germany
Autori CNR e affiliazioni
  • OVIDIO SALVETTI
Lingua/e
  • inglese
SintesiDetailed, consistent semantic annotation of large collections of multimedia data is difficult and time-consuming. In domains such as eScience, digital curation and industrial monitoring, fine-grained high-quality labeling of regions enables advanced semantic querying, analysis and aggregation and supports collaborative research. Manual annotation is inefficient and too subjective to be a viable solution. Automatic solutions are often highly domain or application specific, require large volumes of annotated training corpi and, if using a 'black box' approach, add little to the overall scientific knowledge. This article evaluates the use of simple artificial neural networks to semantically annotate micrographs and discusses the generic process chain necessary for semi-automatic semantic annotation of images.
Lingua sintesieng
Altra sintesi-
Lingua altra sintesi-
Pagine da69
Pagine a79
Pagine totali-
Serie/CollanaLecture notes in computer science
Attiva dal 1973
Editore: Springer - Berlin
Paese di pubblicazione: Germania
Lingua: multilingue
ISSN: 0302-9743
Titolo chiave: Lecture notes in computer science
Titolo proprio: Lecture notes in computer science.
Titolo abbreviato: Lect. notes comput. sci.
Titoli alternativi:
  • Lecture notes in computer science. Lecture notes in artificial intelligence
  • Lecture notes in artificial intelligence
  • LNCS. Lecture notes in computer science (Print)
  • Lecture notes in computer science (Print)
  • Lecture notes in computer science. LNAI. Lecture notes in artificial intelligence
  • Lecture notes in computer science. Lecture notes in bioinformatics (Print)
  • Lecture notes in computer science. Journal subline
Titolo del volumeMDA 2006/2007
Numero volume della serie/collana4826
Curatore/i del volumePetra Perner and Ovidio Salvetti
ISBN978-3-540-76299-7
Edizione/Versione-
DOI-
Editore-
Verificato da referee-
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)-
Parole chiaveMultimedia semantic annotation, Semantic gap, Artificial neural networks
Link (URL, URI)http://www.springerlink.com/content/b4024796wq1625q7/fulltext.pdf
Titolo parallelo-
Note/Altre informazioni-
Strutture CNR
  • ISTI — Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"
Moduli/Attività/Sottoprogetti CNR
  • ICT.P10.012.001 : Elaborazione di segnali e immagini per impieghi diagnostici e interpretazione di immagini multisorgente
Progetti Europei-
Allegati
Semi-automatic semantic tagging of 3D images from pancreas cells (documento privato )
Descrizione: Codice PuMa: cnr.isti/2007-A1-010
Tipo documento: application/pdf

Dati associati a vecchie tipologie
I dati associati a vecchie tipologie non sono modificabili, derivano dal cambiamento della tipologia di prodotto e hanno solo valore storico.
RivistaLecture notes in computer science
Attiva dal 1973
Editore: Springer - Berlin
Paese di pubblicazione: Germania
Lingua: multilingue
ISSN: 0302-9743
Titolo chiave: Lecture notes in computer science
Titolo proprio: Lecture notes in computer science.
Titolo abbreviato: Lect. notes comput. sci.
Titoli alternativi:
  • Lecture notes in computer science. Lecture notes in artificial intelligence
  • Lecture notes in artificial intelligence
  • LNCS. Lecture notes in computer science (Print)
  • Lecture notes in computer science (Print)
  • Lecture notes in computer science. LNAI. Lecture notes in artificial intelligence
  • Lecture notes in computer science. Lecture notes in bioinformatics (Print)
  • Lecture notes in computer science. Journal subline
AbstractDetailed, consistent semantic annotation of large collections of multimedia data is difficult and time-consuming. In domains such as eScience, digital curation and industrial monitoring, fine-grained high-quality labeling of regions enables advanced semantic querying, analysis and aggregation and supports collaborative research. Manual annotation is inefficient and too subjective to be a viable solution. Automatic solutions are often highly domain or application specific, require large volumes of annotated training corpi and, if using a 'black box' approach, add little to the overall scientific knowledge. This article evaluates the use of simple artificial neural networks to semantically annotate micrographs and discusses the generic process chain necessary for semi-automatic semantic annotation of images.
N. volume della rivista4826

Dati storici
I dati storici non sono modificabili, sono stati ereditati da altri sistemi (es. Gestione Istituti, PUMA, ...) e hanno solo valore storico.
Area disciplinareComputer Science & Engineering
Rivista ISILECTURE NOTES IN ARTIFICIAL INTELLIGENCE [06400S0]
NoteIn: MDA 2006/2007. pp. 69 - 79. Petra Perner and Ovidio Salvetti (ed.). (Lecture Notes in Artificial Intelligence, vol. 4826). Springer Verlag, 2007.