Ontology type: schema:Chapter
2010
AUTHORS ABSTRACTThis paper describes a method that learns a variety of features to perform photo annotation. We introduce concept-specific regional features and combine them with global features. The regional features were extracted through a novel region selection algorithm based on Multiple Instance Learning. Supervised classification for photo annotation was learned using Support Vector Machines with extended Gaussian Kernels over the χ2 distance, together with a simple greedy feature selection. The method was evaluated using the ImageCLEF 2009 Photo Annotation task and competitive benchmarking results were achieved. More... »
PAGES287-290
Multilingual Information Access Evaluation II. Multimedia Experiments
ISBN
978-3-642-15750-9
978-3-642-15751-6
http://scigraph.springernature.com/pub.10.1007/978-3-642-15751-6_36
DOIhttp://dx.doi.org/10.1007/978-3-642-15751-6_36
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1034080535
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Artificial Intelligence and Image Processing",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Information and Computing Sciences",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Institute for Infocomm Research",
"id": "https://www.grid.ac/institutes/grid.418705.f",
"name": [
"Institute for Infocomm Research, 1 Fusionopolis Way, #21-01 Connexis (South Tower), 138632, Singapore"
],
"type": "Organization"
},
"familyName": "Ngiam",
"givenName": "Jiquan",
"id": "sg:person.014773731501.87",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014773731501.87"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Institute for Infocomm Research",
"id": "https://www.grid.ac/institutes/grid.418705.f",
"name": [
"Institute for Infocomm Research, 1 Fusionopolis Way, #21-01 Connexis (South Tower), 138632, Singapore"
],
"type": "Organization"
},
"familyName": "Goh",
"givenName": "Hanlin",
"id": "sg:person.01370567162.07",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01370567162.07"
],
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.1007/s11263-006-9794-4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1008205152",
"https://doi.org/10.1007/s11263-006-9794-4"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1145/244130.244148",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1043049254"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1023/b:visi.0000029664.99615.94",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1052687286",
"https://doi.org/10.1023/b:visi.0000029664.99615.94"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tpami.2007.70716",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061743364"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/cvpr.2008.4587586",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1093337684"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/cvpr.2008.4587627",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1094729769"
],
"type": "CreativeWork"
}
],
"datePublished": "2010",
"datePublishedReg": "2010-01-01",
"description": "This paper describes a method that learns a variety of features to perform photo annotation. We introduce concept-specific regional features and combine them with global features. The regional features were extracted through a novel region selection algorithm based on Multiple Instance Learning. Supervised classification for photo annotation was learned using Support Vector Machines with extended Gaussian Kernels over the \u03c72 distance, together with a simple greedy feature selection. The method was evaluated using the ImageCLEF 2009 Photo Annotation task and competitive benchmarking results were achieved.",
"editor": [
{
"familyName": "Peters",
"givenName": "Carol",
"type": "Person"
},
{
"familyName": "Caputo",
"givenName": "Barbara",
"type": "Person"
},
{
"familyName": "Gonzalo",
"givenName": "Julio",
"type": "Person"
},
{
"familyName": "Jones",
"givenName": "Gareth J. F.",
"type": "Person"
},
{
"familyName": "Kalpathy-Cramer",
"givenName": "Jayashree",
"type": "Person"
},
{
"familyName": "M\u00fcller",
"givenName": "Henning",
"type": "Person"
},
{
"familyName": "Tsikrika",
"givenName": "Theodora",
"type": "Person"
}
],
"genre": "chapter",
"id": "sg:pub.10.1007/978-3-642-15751-6_36",
"inLanguage": [
"en"
],
"isAccessibleForFree": false,
"isPartOf": {
"isbn": [
"978-3-642-15750-9",
"978-3-642-15751-6"
],
"name": "Multilingual Information Access Evaluation II. Multimedia Experiments",
"type": "Book"
},
"name": "Learning Global and Regional Features for Photo Annotation",
"pagination": "287-290",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1034080535"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/978-3-642-15751-6_36"
]
},
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"a259e758636aafc962d8011342c7be95c83d52e7b5c082e127e6276344481652"
]
}
],
"publisher": {
"location": "Berlin, Heidelberg",
"name": "Springer Berlin Heidelberg",
"type": "Organisation"
},
"sameAs": [
"https://doi.org/10.1007/978-3-642-15751-6_36",
"https://app.dimensions.ai/details/publication/pub.1034080535"
],
"sdDataset": "chapters",
"sdDatePublished": "2019-04-16T08:24",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000363_0000000363/records_70043_00000001.jsonl",
"type": "Chapter",
"url": "https://link.springer.com/10.1007%2F978-3-642-15751-6_36"
}
]Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-15751-6_36'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-15751-6_36'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-15751-6_36'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-15751-6_36'
This table displays all metadata directly associated to this object as RDF triples.
122 TRIPLES
23 PREDICATES
33 URIs
20 LITERALS
8 BLANK NODES