Supergraph models: a novel approach for structure learning, classification and recognition
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis Book |
| Language: | English |
| Published: |
Münster
Verl.-Haus Monsenstein und Vannerdat
2013
|
| Series: | MV Wissenschaft
|
| Subjects: | |
| Online Access: | Inhaltstext Inhaltsverzeichnis |
| Physical Description: | XVII, 185 S. Ill., graph. Darst. |
| ISBN: | 9783869918259 386991825X |
Staff View
MARC
| LEADER | 00000nam a2200000 c 4500 | ||
|---|---|---|---|
| 001 | BV041213355 | ||
| 003 | DE-604 | ||
| 007 | t | ||
| 008 | 130809s2013 ad|| m||| 00||| eng d | ||
| 015 | |a 13,N16 |2 dnb | ||
| 015 | |a 13,A26 |2 dnb | ||
| 016 | 7 | |a 1033300454 |2 DE-101 | |
| 020 | |a 9783869918259 |c kart. : EUR 19.00 (DE), EUR 19.60 (AT), sfr 27.50 (freier Pr.) |9 978-3-86991-825-9 | ||
| 020 | |a 386991825X |9 3-86991-825-X | ||
| 024 | 3 | |a 9783869918259 | |
| 035 | |a (OCoLC)851074140 | ||
| 035 | |a (DE-599)DNB1033300454 | ||
| 040 | |a DE-604 |b ger |e rakddb | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-188 | ||
| 082 | 0 | |a 006.31 |2 22/ger | |
| 084 | |a 004 |2 sdnb | ||
| 084 | |a 510 |2 sdnb | ||
| 100 | 1 | |a Hartz, Johannes |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Supergraph models |b a novel approach for structure learning, classification and recognition |c by Johannes Hartz |
| 264 | 1 | |a Münster |b Verl.-Haus Monsenstein und Vannerdat |c 2013 | |
| 300 | |a XVII, 185 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a MV Wissenschaft | |
| 502 | |a Hamburg, Univ., Diss., 2012 | ||
| 650 | 0 | 7 | |a Graphisches Modell |0 (DE-588)4606156-3 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Automatische Klassifikation |0 (DE-588)4120957-6 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Mustererkennung |0 (DE-588)4040936-3 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Strukturlernen |0 (DE-588)4691220-4 |2 gnd |9 rswk-swf |
| 655 | 7 | |0 (DE-588)4113937-9 |a Hochschulschrift |2 gnd-content | |
| 689 | 0 | 0 | |a Strukturlernen |0 (DE-588)4691220-4 |D s |
| 689 | 0 | 1 | |a Mustererkennung |0 (DE-588)4040936-3 |D s |
| 689 | 0 | 2 | |a Automatische Klassifikation |0 (DE-588)4120957-6 |D s |
| 689 | 0 | 3 | |a Graphisches Modell |0 (DE-588)4606156-3 |D s |
| 689 | 0 | |5 DE-604 | |
| 856 | 4 | 2 | |m X:MVB |q text/html |u http://deposit.dnb.de/cgi-bin/dokserv?id=4294830&prov=M&dok_var=1&dok_ext=htm |3 Inhaltstext |
| 856 | 4 | 2 | |m DNB Datenaustausch |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026188038&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-026188038 | |
Record in the Search Index
| _version_ | 1809768753515200512 |
|---|---|
| adam_text |
IMAGE 1
C O N T E N T S
LIST O F T A B L E S X I I I
LIST O F F I G U R E S X V
1 I N T R O D U C T I O N 1
1.1 S T R U C T U R E RECOGNITION 4
1.2 GOAL A N D PROBLEM STATEMENT. 7
1.3 SHORT S U M M A R Y OF RESULTS 8
1.4 PREVIEW OF THESIS WORK 10
2 R E L A T E D W O R K 1 1
2.1 S T R U C T U R E MODEL LEARNING 13
2.1.1 BLOCKS WORLD 13
2.1.2 VERSION SPACE LEARNING 14
2.1.3 S U B D U E A N D S U B D U E C L 15
2.1.4 INDUCTIVE LOGIC P R O G R A M M I N G 16
2.2 S T R U C T U R E MODELLING 17
2.2.1 GRAPHICAL MODELS 17
2.2.1.1 MARKOV R A N D O M FIELDS 18
2.2.1.2 BAYESIAN COMPOSITIONAL HIERARCHIES 11)
2.2.1.3 HIDDEN MARKOV MODELS 20
2.2.1.4 S T R U C T U R E LEARNING FOR GRAPHICAL MODELS 20
2.2.2 CONTEXT FREE G R A M M A R S 21
2.3 S T R U C T U R E CLASSIFICATION 22
2.3.1 G R A P H KERNELS 22
2.3.2 KERNEL S U P P O R T VECTOR MACHINES 23
2.3.3 RECURRENT NEURAL NETWORKS 23
2.4 SCENE INTERPRETATION SYSTEMS 25
2.4.1 CRISP INTERPRETATION 25
2.4.2 HYBRID INTERPRETATION 2T
2.4.2.1 S C E N I C 27
2.4.2.2 SCENIOR 28
2.4.2.3 STOCHASTIC G R A M M A R S 30
2.5 S U M M A R Y 30
3 S U P E R G R A P H M O D E L S 3 3
3.1 MODEL REPRESENTATION 33
3.1.1 S T R U C T U R E G R A P H 34
I X
HTTP://D-NB.INFO/1033300454
IMAGE 2
C O N T E N T S
3.1.1.1 A T T R I B U T E VALUE DOMAINS 37
SYMBOLIC DOMAINS 38
RANGE DOMAINS 3!)
3 .1 .1.2 MAXIMUM C O M M O N GCNERALISABLE SUBGRAPH 39
3.1.1.3 STRUCTURE G R A P H CLASSIFICATION 42
3.1.2 OBSERVATION HISTOGRAM 42
3.1.2.1 EXACT OBSERVATIONS 45
3.1.2.2 GENERALISED OBSERVATIONS 4(I
3.1.2.3 COMPARISON A N D DISCUSSION 49
3.1.2.4 EVALUATION ON SYNTHETIC D A T A 53
3.1.2.5 MODEL PRIORS 54
3.1.2.(I LIKELIHOOD MAXIMISATION 55
3.1.3 MODEL DEFINITION A N D S U M M A R Y 56
3.2 MODEL LEARNING 56
3.2.1 OUTLINE 57
3.2.2 A T T R I B U T E GENERALISATION COST FUNCTION 58
3.2.3 STRUCTURE G R A P H GENERALISATION 5!)
3.2.4 A T T R I B U T E VALUE GENERALISATION (IL
3.2.5 OBSERVATION HISTOGRAM U P D A T E 62
3.3 LEARNING FROM NEGATIVE EXAMPLES 62
3.4 INDUCTIVE BIAS 64
3.5 COMPLEXITY ANALYSIS A N D SCALABILITY 65
3.6 EVALUATION OF OPTIMALITV 66
3.7 (LOSSLESS) ATTRIBUTED G R A P H COMPRESSION 67
3.8 S U M M A R Y A N D CONCLUSIONS 68
4 A P P L I C A T I O N O F L E A R N T M O D E L S 7 1
4.1 M A X I M U M A-POSTERIORI PROBABILITY CLASSIFICATION OF O B J E C T
STRUCTURES 72
4.2 CLUSTERING OF OBJECT STRUCTURES 73
4.3 MULTI-CLASSIFIC ATION SCENARIOS 75
4.3.1 MULTI-MODEL SCALING 76
4.3.2 ONE-SHOT LEARNING EXPERIMENTS 78
4.4 RECOGNITION OF OBJECT STRUCTURES 7!)
4.4.1 PROBLEM DEFINITION 82
4.4.2 OUTLINE 83
4.4.3 PROBABILISTIC FRAMEWORK 85
4.4.4 BOTTOM-UP COMPOSITIONAL S T R U C T U R E RECOGNITION 86
4.4.5 COMPLEXITY ANALYSIS 87
4.4.6 DATA-INDEPENDENT, SEARCH SPACE OPTIMISATION 88
4.4.6.1 LEVEHVISE OPTIMISATION 88
4.4.6.2 GLOBAL OPTIMISATION 8!)
4.4.7 DATA-DEPENDENT SEARCH SPACE OPTIMISATION 8!)
4.4.7.1 ETR.IMS DATASET 90
4.4.7.2 CONLL DATASET; 90
4.4.8 STRUCTURE RECOGNITION SCORE 90
IMAGE 3
C O N T E N T S XI
5 E X P E R I M E N T A L E V A L U A T I O N 9 3
* R .L BENCHMARK DATA.SET,S 93
5.1.1 ETR.IMS S A M E INTERPRETATION DATA,SET 94
5.1.1.1 D A T A DESCRIPTION 95
5.1.1.2 A T T R I B U T E VALUE DOMAINS !)!)
5.1.2 M U T A G MUTAGENICITY PREDICTION DATASET 101
5.1.2.1 D A T A DESCRIPTION 101
5.1.2.2 A T T R I B U T E VALUE DOMAINS 102
5.1.3 CONLL TEXT CHUNKING DATASET 103
5.1.3.1 D A T A DESCRIPTION 104
5.1.3.2 A T T R I B U T E VALUE DOMAINS 105
5.1.4 C O F R I E N D AIRPORT, SERVICE EVENT DATASET 107
5.1.4.1 D A T A DESCRIPTION 108
5.1.4.2 A T T R I B U T E VALUE DOMAINS 10!)
5.2 S T R U C T U R E CLASSIFICATION EXPERIMENTS 113
5.2.1 CLASSIFICATION OF FACADE STRUCTURES 114
5.2.1.1 ONE-SHOT. LEARNING 118
5.2.1.2 DISCUSSION 119
5.2.2 CLASSIFICATION OF MOLECULES 120
5.2.2.1 ONE-SHOT. LEARNING 123
5.2.2.2 DISCUSSION 124
5.2.3 CLASSIFICATION OF TEXT CHUNKS 125
5.2.3.1 DISCUSSION 129
5.2.4 CLASSIFICATION OF AIRPORT, SERVICE ACTIONS 129
5.2.4.1 DISCUSSION 132
5.3 STRUCTURE; RECOGNITION EXPERIMENTS 133
5.3.1 RECOGNITION OF FACADE STRUCTURES 133
5.3.1.1 DISCUSSION 148
5.3.2 RECOGNITION OF TEXT CHUNKS 149
5.3.2.1 DISCUSSION 154
5.3.3 RECOGNITION OF AIRPORT SERVICE ACTIONS 155
5.4 S T R U C T U R E PREDICTION EXPERIMENTS 15(5
5.4.1 PREDICTION OF MOLECULES 15(5
5.4.1.1 DISCUSSION 159
5.5 S U M M A R Y 1( 1
6 C O N C L U S I O N S 1 6 5
FI.L S U M M A R Y OF RESULTS LF (
(I.2 O P E N ISSUES 1(58
(I.3 COMPARISON T O O T H E R WORK 1( 9
FT.4 FURTHER WORK 170
6.5 OUTLOOK 171
B I B L I O G R A P H Y 1 7 3 |
| any_adam_object | 1 |
| author | Hartz, Johannes |
| author_facet | Hartz, Johannes |
| author_role | aut |
| author_sort | Hartz, Johannes |
| author_variant | j h jh |
| building | Verbundindex |
| bvnumber | BV041213355 |
| ctrlnum | (OCoLC)851074140 (DE-599)DNB1033300454 |
| dewey-full | 006.31 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.31 |
| dewey-search | 006.31 |
| dewey-sort | 16.31 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik Mathematik |
| format | Thesis Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nam a2200000 c 4500</leader><controlfield tag="001">BV041213355</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="007">t</controlfield><controlfield tag="008">130809s2013 ad|| m||| 00||| eng d</controlfield><datafield tag="015" ind1=" " ind2=" "><subfield code="a">13,N16</subfield><subfield code="2">dnb</subfield></datafield><datafield tag="015" ind1=" " ind2=" "><subfield code="a">13,A26</subfield><subfield code="2">dnb</subfield></datafield><datafield tag="016" ind1="7" ind2=" "><subfield code="a">1033300454</subfield><subfield code="2">DE-101</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9783869918259</subfield><subfield code="c">kart. : EUR 19.00 (DE), EUR 19.60 (AT), sfr 27.50 (freier Pr.)</subfield><subfield code="9">978-3-86991-825-9</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">386991825X</subfield><subfield code="9">3-86991-825-X</subfield></datafield><datafield tag="024" ind1="3" ind2=" "><subfield code="a">9783869918259</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)851074140</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DNB1033300454</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rakddb</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-188</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.31</subfield><subfield code="2">22/ger</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">004</subfield><subfield code="2">sdnb</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">510</subfield><subfield code="2">sdnb</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Hartz, Johannes</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Supergraph models</subfield><subfield code="b">a novel approach for structure learning, classification and recognition</subfield><subfield code="c">by Johannes Hartz</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Münster</subfield><subfield code="b">Verl.-Haus Monsenstein und Vannerdat</subfield><subfield code="c">2013</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">XVII, 185 S.</subfield><subfield code="b">Ill., graph. Darst.</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">MV Wissenschaft</subfield></datafield><datafield tag="502" ind1=" " ind2=" "><subfield code="a">Hamburg, Univ., Diss., 2012</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Graphisches Modell</subfield><subfield code="0">(DE-588)4606156-3</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Automatische Klassifikation</subfield><subfield code="0">(DE-588)4120957-6</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Mustererkennung</subfield><subfield code="0">(DE-588)4040936-3</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Strukturlernen</subfield><subfield code="0">(DE-588)4691220-4</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="0">(DE-588)4113937-9</subfield><subfield code="a">Hochschulschrift</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Strukturlernen</subfield><subfield code="0">(DE-588)4691220-4</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Mustererkennung</subfield><subfield code="0">(DE-588)4040936-3</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="2"><subfield code="a">Automatische Klassifikation</subfield><subfield code="0">(DE-588)4120957-6</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="3"><subfield code="a">Graphisches Modell</subfield><subfield code="0">(DE-588)4606156-3</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="m">X:MVB</subfield><subfield code="q">text/html</subfield><subfield code="u">http://deposit.dnb.de/cgi-bin/dokserv?id=4294830&prov=M&dok_var=1&dok_ext=htm</subfield><subfield code="3">Inhaltstext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="m">DNB Datenaustausch</subfield><subfield code="q">application/pdf</subfield><subfield code="u">http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026188038&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA</subfield><subfield code="3">Inhaltsverzeichnis</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-026188038</subfield></datafield></record></collection> |
| genre | (DE-588)4113937-9 Hochschulschrift gnd-content |
| genre_facet | Hochschulschrift |
| id | DE-604.BV041213355 |
| illustrated | Illustrated |
| indexdate | 2024-09-10T00:59:38Z |
| institution | BVB |
| isbn | 9783869918259 386991825X |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-026188038 |
| oclc_num | 851074140 |
| open_access_boolean | |
| owner | DE-188 |
| owner_facet | DE-188 |
| physical | XVII, 185 S. Ill., graph. Darst. |
| publishDate | 2013 |
| publishDateSearch | 2013 |
| publishDateSort | 2013 |
| publisher | Verl.-Haus Monsenstein und Vannerdat |
| record_format | marc |
| series2 | MV Wissenschaft |
| spelling | Hartz, Johannes Verfasser aut Supergraph models a novel approach for structure learning, classification and recognition by Johannes Hartz Münster Verl.-Haus Monsenstein und Vannerdat 2013 XVII, 185 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier MV Wissenschaft Hamburg, Univ., Diss., 2012 Graphisches Modell (DE-588)4606156-3 gnd rswk-swf Automatische Klassifikation (DE-588)4120957-6 gnd rswk-swf Mustererkennung (DE-588)4040936-3 gnd rswk-swf Strukturlernen (DE-588)4691220-4 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Strukturlernen (DE-588)4691220-4 s Mustererkennung (DE-588)4040936-3 s Automatische Klassifikation (DE-588)4120957-6 s Graphisches Modell (DE-588)4606156-3 s DE-604 X:MVB text/html http://deposit.dnb.de/cgi-bin/dokserv?id=4294830&prov=M&dok_var=1&dok_ext=htm Inhaltstext DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026188038&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Hartz, Johannes Supergraph models a novel approach for structure learning, classification and recognition Graphisches Modell (DE-588)4606156-3 gnd Automatische Klassifikation (DE-588)4120957-6 gnd Mustererkennung (DE-588)4040936-3 gnd Strukturlernen (DE-588)4691220-4 gnd |
| subject_GND | (DE-588)4606156-3 (DE-588)4120957-6 (DE-588)4040936-3 (DE-588)4691220-4 (DE-588)4113937-9 |
| title | Supergraph models a novel approach for structure learning, classification and recognition |
| title_auth | Supergraph models a novel approach for structure learning, classification and recognition |
| title_exact_search | Supergraph models a novel approach for structure learning, classification and recognition |
| title_full | Supergraph models a novel approach for structure learning, classification and recognition by Johannes Hartz |
| title_fullStr | Supergraph models a novel approach for structure learning, classification and recognition by Johannes Hartz |
| title_full_unstemmed | Supergraph models a novel approach for structure learning, classification and recognition by Johannes Hartz |
| title_short | Supergraph models |
| title_sort | supergraph models a novel approach for structure learning classification and recognition |
| title_sub | a novel approach for structure learning, classification and recognition |
| topic | Graphisches Modell (DE-588)4606156-3 gnd Automatische Klassifikation (DE-588)4120957-6 gnd Mustererkennung (DE-588)4040936-3 gnd Strukturlernen (DE-588)4691220-4 gnd |
| topic_facet | Graphisches Modell Automatische Klassifikation Mustererkennung Strukturlernen Hochschulschrift |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=4294830&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026188038&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT hartzjohannes supergraphmodelsanovelapproachforstructurelearningclassificationandrecognition |