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pro vyhledávání: '"Simon-Martin Schroder"'
Publikováno v:
IEEE Access, Vol 9, Pp 82146-82168 (2021)
While deep learning strategies achieve outstanding results in computer vision tasks, one issue remains: The current strategies rely heavily on a huge amount of labeled data. In many real-world problems, it is not feasible to create such an amount of
Externí odkaz:
https://doaj.org/article/19eacb9697b84a03ab19befee1c03787
Publikováno v:
IEEE Access, Vol 9, Pp 82146-82168 (2021)
While deep learning strategies achieve outstanding results in computer vision tasks, one issue remains: The current strategies rely heavily on a huge amount of labeled data. In many real-world problems, it is not feasible to create such an amount of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::534ee864a5eae7e24a257fd5a1117b99
http://arxiv.org/abs/2002.08721
http://arxiv.org/abs/2002.08721
Autor:
Simon-Martin Schröder, Rainer Kiko
Publikováno v:
Sensors, Vol 22, Iss 7, p 2775 (2022)
Image annotation is a time-consuming and costly task. Previously, we published MorphoCluster as a novel image annotation tool to address problems of conventional, classifier-based image annotation approaches: their limited efficiency, training set bi
Externí odkaz:
https://doaj.org/article/1b1c33c340c94eaba45e6ff004c1dec5
Autor:
Lars Schmarje, Johannes Brünger, Monty Santarossa, Simon-Martin Schröder, Rainer Kiko, Reinhard Koch
Publikováno v:
Sensors, Vol 21, Iss 19, p 6661 (2021)
Deep learning has been successfully applied to many classification problems including underwater challenges. However, a long-standing issue with deep learning is the need for large and consistently labeled datasets. Although current approaches in sem
Externí odkaz:
https://doaj.org/article/f46ca07e0a63421bb7a7eec7f858b666
Publikováno v:
Sensors, Vol 20, Iss 11, p 3060 (2020)
In this work, we present MorphoCluster, a software tool for data-driven, fast, and accurate annotation of large image data sets. While already having surpassed the annotation rate of human experts, volume and complexity of marine data will continue t
Externí odkaz:
https://doaj.org/article/a50ff817ecdd41898201aaa9731d8938