Anomaliedetektion in räumlich-zeitlichen Datensätzen
Human support in surveillance tasks is crucial due to the overwhelming amount of sensor data. This work focuses on the development of data fusion methods using the maritime domain as an example. Various anomalies are investigated, evaluated using real vessel traffic data and tested with experts. For...
में बचाया:
| मुख्य लेखक: | |
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| स्वरूप: | Online |
| भाषा: | जर्मन |
| प्रकाशित: |
KIT Scientific Publishing
2023
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| विषय: | |
| ऑनलाइन पहुंच: | OCN: 1403109722 |
| टैग: |
कोई टैग नहीं, इस रिकॉर्ड को टैग करने वाले पहले व्यक्ति बनें!
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| _version_ | 1869523944677048320 |
|---|---|
| author | Anneken, Mathias |
| author_browse | Anneken, Mathias |
| author_facet | Anneken, Mathias |
| author_sort | Anneken, Mathias |
| collection | Directory of Open Access Books |
| description | Human support in surveillance tasks is crucial due to the overwhelming amount of sensor data. This work focuses on the development of data fusion methods using the maritime domain as an example. Various anomalies are investigated, evaluated using real vessel traffic data and tested with experts. For this purpose, situations of interest and anomalies are modelled and evaluated based on different machine learning methods. |
| format | Online |
| id | doab-20.500.12854ir-122253 |
| institution | Directory of Open Access Books |
| language | ger |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | KIT Scientific Publishing |
| publisherStr | KIT Scientific Publishing |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1222532025-05-27T07:46:31Z Anomaliedetektion in räumlich-zeitlichen Datensätzen Anneken, Mathias spatio-temporal data; situation analysis; anomaly detection; räumlich-zeitliche Daten; Maritime Überwachung; Anomaliedetektion; maritime surveillance; Situationsanalyse; machine learning; Maschinelles Lernen Human support in surveillance tasks is crucial due to the overwhelming amount of sensor data. This work focuses on the development of data fusion methods using the maritime domain as an example. Various anomalies are investigated, evaluated using real vessel traffic data and tested with experts. For this purpose, situations of interest and anomalies are modelled and evaluated based on different machine learning methods. 2023-11-17T09:53:49Z 2023-11-17T09:53:49Z 2023-08-29T07:29:03Z 2023 book OCN: 1403109722 https://library.oapen.org/handle/20.500.12657/75885 9783731513001 https://directory.doabooks.org/handle/20.500.12854/122253 ger Karlsruher Schriften zur Anthropomatik open access image/jpeg image/jpeg image/jpeg image/jpeg image/jpeg image/jpeg Attribution 4.0 International Attribution 4.0 International Attribution 4.0 International Attribution 4.0 International Attribution 4.0 International Attribution 4.0 International https://library.oapen.org/bitstream/20.500.12657/75885/1/anomaliedetektion-in-raumlich-zeitlichen-datensatzen.pdf https://library.oapen.org/bitstream/20.500.12657/75885/1/anomaliedetektion-in-raumlich-zeitlichen-datensatzen.pdf https://library.oapen.org/bitstream/20.500.12657/75885/1/anomaliedetektion-in-raumlich-zeitlichen-datensatzen.pdf https://library.oapen.org/bitstream/20.500.12657/75885/1/anomaliedetektion-in-raumlich-zeitlichen-datensatzen.pdf https://library.oapen.org/bitstream/20.500.12657/75885/1/anomaliedetektion-in-raumlich-zeitlichen-datensatzen.pdf https://library.oapen.org/bitstream/20.500.12657/75885/1/anomaliedetektion-in-raumlich-zeitlichen-datensatzen.pdf KIT Scientific Publishing 10.5445/KSP/1000158519 10.5445/KSP/1000158519 68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2 9783731513001 AG Universitätsverlage 264 open access |
| spellingShingle | spatio-temporal data; situation analysis; anomaly detection; räumlich-zeitliche Daten; Maritime Überwachung; Anomaliedetektion; maritime surveillance; Situationsanalyse; machine learning; Maschinelles Lernen Anneken, Mathias Anomaliedetektion in räumlich-zeitlichen Datensätzen |
| title | Anomaliedetektion in räumlich-zeitlichen Datensätzen |
| title_full | Anomaliedetektion in räumlich-zeitlichen Datensätzen |
| title_fullStr | Anomaliedetektion in räumlich-zeitlichen Datensätzen |
| title_full_unstemmed | Anomaliedetektion in räumlich-zeitlichen Datensätzen |
| title_short | Anomaliedetektion in räumlich-zeitlichen Datensätzen |
| title_sort | anomaliedetektion in raumlich zeitlichen datensatzen |
| topic | spatio-temporal data; situation analysis; anomaly detection; räumlich-zeitliche Daten; Maritime Überwachung; Anomaliedetektion; maritime surveillance; Situationsanalyse; machine learning; Maschinelles Lernen |
| topic_facet | spatio-temporal data; situation analysis; anomaly detection; räumlich-zeitliche Daten; Maritime Überwachung; Anomaliedetektion; maritime surveillance; Situationsanalyse; machine learning; Maschinelles Lernen |
| url | OCN: 1403109722 |
| work_keys_str_mv | AT annekenmathias anomaliedetektioninraumlichzeitlichendatensatzen |