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Konstantin Olschofsky

Biographic Data

ID6705047
NAMEKonstantin Olschofsky
GIVEN NAMESKonstantin
FAMILY NAMEOlschofsky
SIGNATUREOLSCHOFSKY K
AFFILIATIONSUniversität Hamburg
ORCID0000-0002-7289-984X
VERIFIEDYes
TOTAL WORKS2
TOTAL CITATIONS3
WORKS AS AUTHOR2
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2018
LATEST PUBLICATION YEAR2020
H-INDEX1
  • Rapid field identification of cites timber species by deep learning

    Open Access•Konstantin Olschofsky, Michael Kohl•ARTICLE•Trees Forests and People•2020

    Enforcement of the ban on trade in protected tree species is often hampered by insufficient knowledge of species identification by the authorities responsible for control. We present a new method based on a deep learning approach that facilitates the separation of protected and non protected tree species. The classification system used here is based on the image classification model Inception-v3, a so-called transfer learning tool provided by Goo…

  • Opportunity costs of conserving a dry tropical forest under Redd

    Open Access•Regina Neudert, Konstantin Olschofsky et al.•ARTICLE•Forest Policy and Economics•2018•Cited by: 3•References: 12

  • Opportunity costs of conserving a dry tropical forest under Redd

    Open Access•Regina Neudert, Konstantin Olschofsky et al.•ARTICLE•Forest Policy and Economics•2018•Cited by: 3•References: 12

  • Opportunity costs of conserving a dry tropical forest under Redd

    Open Access•Regina Neudert, Konstantin Olschofsky et al.•ARTICLE•Forest Policy and Economics•2018•Cited by: 3•References: 12

  • Rapid field identification of cites timber species by deep learning

    Open Access•Konstantin Olschofsky, Michael Kohl•ARTICLE•Trees Forests and People•2020

    Enforcement of the ban on trade in protected tree species is often hampered by insufficient knowledge of species identification by the authorities responsible for control. We present a new method based on a deep learning approach that facilitates the separation of protected and non protected tree species. The classification system used here is based on the image classification model Inception-v3, a so-called transfer learning tool provided by Goo…

Agriculture (1 work) · Agroforestry (1 work) · Artificial Intelligence (1 work) · Bottleneck (1 work) · Business (1 work) · Carbon sequestration (1 work) · Computer Science (1 work) · Conservation, Biodiversity, and Resource Management (1 work) · Contextual image classification (1 work) · Convolutional neural network (1 work)

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