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2014 - 20194
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İndeks: Conference Proceedings Citation Index – Science (CPCI-S) × Konu: Forestry ×

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Listeleniyor 1 - 4 / 4
  • Küçük Resim
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    A precision estimation method for volumetric changes
    (IEEE, 2019-06) Akça, Mehmet Devrim; Stylianidis, Efstratios; Gruen, Armin W.; Altan, Mehmet Orhan; Hofer, Martin; Smagas, Konstantinos; Sanchez Martin, Victor; Walli, Andreas; Jimeno, Elisa; Garcia, Alejandro
    Earth surface changes are often computed by comparing the sequences of digital elevation models (DEMs) so called the DEM of difference (DoD) method. We present an operational DEM generation, co-registration and DoD comparison software in which the surface changes are quantified in metric units of volume. A practical method, which is based on the law of error propagation, is developed to estimate the theoretical precisions of volumetric changes. The proposed pipeline can estimate the change of object volumes (in terms of loss and gain) together with their precision numbers. Change of the forest volume in a fire effected region in a test site is analyzed for the validation. The method can be used for various change detection applications related to forestry as well as other topics such as earthworks, geomorphology, mining, and urbanization.
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    Chunking in Turkish with conditional random fields
    (Springer-Verlag, 2015-04-14) Yıldız, Olcay Taner; Solak, Ercan; Ehsani, Razieh; Görgün, Onur
    In this paper, we report our work on chunking in Turkish. We used the data that we generated by manually translating a subset of the Penn Treebank. We exploited the already available tags in the trees to automatically identify and label chunks in their Turkish translations. We used conditional random fields (CRF) to train a model over the annotated data. We report our results on different levels of chunk resolution.
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    Constructing a Turkish-English parallel treebank
    (Association for Computational Linguistics (ACL), 2014) Yıldız, Olcay Taner; Solak, Ercan; Görgün, Onur; Ehsani, Razieh
    In this paper, we report our preliminary efforts in building an English-Turkish parallel treebank corpus for statistical machine translation. In the corpus, we manually generated parallel trees for about 5,000 sentences from Penn Treebank. English sentences in our set have a maximum of 15 tokens, including punctuation. We constrained the translated trees to the reordering of the children and the replacement of the leaf nodes with appropriate glosses. We also report the tools that we built and used in our tree translation task.
  • Küçük Resim
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    An all-words sense annotated Turkish corpus
    (IEEE, 2018-06-06) Akçakaya, Sinan; Yıldız, Olcay Taner
    This paper reports our efforts in constructing of a sense labeled Turkish corpus with respect to Turkish Language Institution's dictionary, using the traditional method of manual tagging. We tagged a pre-built parallel treebank which is translated from the Penn Treebank II corpus. This approach allowed us to generate a full-coverage resource, in which syntactic and semantic information merged. We also provide miscellaneous statistics about the corpus itself as well as its development process.