Using historical maps in scientific studies: applications, challenges, and best practices
Gespeichert in:
| Beteiligte Personen: | , , |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Cham, Switzerland
Springer
[2020]
|
| Schriftenreihe: | SpringerBriefs in geography
|
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=031477248&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | x, 114 Seiten Illustrationen, Diagramme, Karten |
| ISBN: | 9783319669076 |
Internformat
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Datensatz im Suchindex
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|---|---|
| adam_text | Contents 1 Introduction................................................................................................... 1.1 Book Objectives..................................................................................... 1.2 Book Structure....................................................................................... References....................................................................................................... 1 1 7 7 2 Historical Map Applications and ProcessingTechnologies..................... 2.1 Introduction........................................................................................... 2.2 Applications of Historical Maps............................................................ 2.3 Case Studies of Map Processing Technologies................................... 2.3.1 Case Study I: Semi-Automatic Symbol Recognition from Map Scans......................................................................... 2.3.2 Case Study II: Multi-Model, Context-Based Automatic Symbol Recognition from Map Scans..................................... 2.3.3 Case Study Discussion and Outlook........................................ 2.4 Chapter Summary................................................................................... References....................................................................................................... 9 10 13 19 3 Creating Structured, Linked GeographicData fromHistorical Maps: Challenges and Trends..................................................................... 3.1 Introduction
........................................................................................... 3.2 Finding Relevant Historical Maps........................................................ 3.3 Converting Map Content to Machine-Readable Formats and Record Uncertainty................................................................................ 3.3.1 Crowdsourcing Approaches..................................................... 3.3.2 Semi-automatic Approaches.................................................... 3.3.3 Multi-Model, Context-Based,Automatic Approaches............ 3.4 Modeling and Publishing Map Content............................................... 3.5 Chapter Summary................................................................................... References........................................................................................................ 21 29 32 33 34 37 37 43 46 47 49 51 55 59 60 ix
x 4 5 Contents Training Deep Learning Models for Geographic Feature Recognition from Historical Maps............................................................. 4.1 Introduction ........................................................................................... 4.2 Challenges in Using CNNs on Historical Maps.................................. 4.2.1 Accurate Boundary Delineation of Geographic Features...... 4.2.2 Scarce Training Data for Cartographic Documents................ 4.3 Overview of Semantic Segmentation for Geographic Feature Recognition from Map Scans................................................................ 4.3.1 VGG16: The 16-layer Very Deep Convolutional Networks for Large-Scale Image Recognition....................... 4.3.2 GoogLeNet................................................................................. 4.3.3 ResNet........................................................................................ 4.3.4 The Encoder and Decoder Architecture for Semantic Segmentation.............................................................................. 4.3.5 Multi-Scale Pyramids of Feature Images for Semantic Segmentation.............................................................................. 4.4 Overview of Transfer Learning for Geographic Feature Recognition from Map Scans................................................................ 4.5 Experiment............................................................................................. 4.5.1 Experimental Data, Settings and Evaluation Metrics............. 4.5.2 Experiment I: The
Impact of Backbone CNNs: FCN-VGG16, FCN-GoogLeNet, and FCN-ResNet.............. 4.5.3 Experiment II: The Impact of Transfer Learning Strategies: PSPNet..................................................................... 4.6 Chapter Summary................................................................................... References........................................................................................................ 89 96 96 Summary and Discussion............................................................................ 5.1 Book Summary....................................................................................... 99 99 A Railroad Recognition Results 65 66 67 69 70 74 75 77 78 79 82 84 85 86 88 101
|
| any_adam_object | 1 |
| author | Chiang, Yao-Yi Duan, Weiwei Leyk, Stefan 1975- |
| author_GND | (DE-588)1204062811 (DE-588)132353415 |
| author_facet | Chiang, Yao-Yi Duan, Weiwei Leyk, Stefan 1975- |
| author_role | aut aut aut |
| author_sort | Chiang, Yao-Yi |
| author_variant | y y c yyc w d wd s l sl |
| building | Verbundindex |
| bvnumber | BV046096393 |
| classification_rvk | RB 10104 |
| ctrlnum | (OCoLC)1135373442 (DE-599)BVBBV046096393 |
| discipline | Geographie |
| format | Book |
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| indexdate | 2024-12-20T18:43:03Z |
| institution | BVB |
| isbn | 9783319669076 |
| language | English |
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| physical | x, 114 Seiten Illustrationen, Diagramme, Karten |
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| publishDate | 2020 |
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| publishDateSort | 2020 |
| publisher | Springer |
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| series2 | SpringerBriefs in geography |
| spellingShingle | Chiang, Yao-Yi Duan, Weiwei Leyk, Stefan 1975- Using historical maps in scientific studies applications, challenges, and best practices Digitalisierung (DE-588)4123065-6 gnd Geschichtswissenschaft (DE-588)4020535-6 gnd Naturwissenschaften (DE-588)4041421-8 gnd Datensammlung (DE-588)4148875-1 gnd Geoinformatik (DE-588)7571300-7 gnd Sozialwissenschaften (DE-588)4055916-6 gnd Kartenauswertung (DE-588)4193951-7 gnd Historische Karte (DE-588)4238091-1 gnd |
| subject_GND | (DE-588)4123065-6 (DE-588)4020535-6 (DE-588)4041421-8 (DE-588)4148875-1 (DE-588)7571300-7 (DE-588)4055916-6 (DE-588)4193951-7 (DE-588)4238091-1 |
| title | Using historical maps in scientific studies applications, challenges, and best practices |
| title_auth | Using historical maps in scientific studies applications, challenges, and best practices |
| title_exact_search | Using historical maps in scientific studies applications, challenges, and best practices |
| title_full | Using historical maps in scientific studies applications, challenges, and best practices Yao-Yi Chiang, Weiwei Duan, Stefan Leyk, Johannes H. Uhl, Craig A. Knoblock |
| title_fullStr | Using historical maps in scientific studies applications, challenges, and best practices Yao-Yi Chiang, Weiwei Duan, Stefan Leyk, Johannes H. Uhl, Craig A. Knoblock |
| title_full_unstemmed | Using historical maps in scientific studies applications, challenges, and best practices Yao-Yi Chiang, Weiwei Duan, Stefan Leyk, Johannes H. Uhl, Craig A. Knoblock |
| title_short | Using historical maps in scientific studies |
| title_sort | using historical maps in scientific studies applications challenges and best practices |
| title_sub | applications, challenges, and best practices |
| topic | Digitalisierung (DE-588)4123065-6 gnd Geschichtswissenschaft (DE-588)4020535-6 gnd Naturwissenschaften (DE-588)4041421-8 gnd Datensammlung (DE-588)4148875-1 gnd Geoinformatik (DE-588)7571300-7 gnd Sozialwissenschaften (DE-588)4055916-6 gnd Kartenauswertung (DE-588)4193951-7 gnd Historische Karte (DE-588)4238091-1 gnd |
| topic_facet | Digitalisierung Geschichtswissenschaft Naturwissenschaften Datensammlung Geoinformatik Sozialwissenschaften Kartenauswertung Historische Karte |
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