Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Mehmet Ozgur Turkoglu"'
Autor:
Gregor Perich, Mehmet Ozgur Turkoglu, Lukas Valentin Graf, Jan Dirk Wegner, Helge Aasen, Achim Walter, Frank Liebisch
Publikováno v:
Field Crops Research, 292
Mapping and predicting crop yield on a large scale is increasingly important for use cases such as policy-making, risk insurance and precision agriculture applications at farm and field scale. The higher spatial resolution of Sentinel-2 compared to L
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a612a5368d7215f32ab02a6d9c1b3e86
https://doi.org/10.1016/j.fcr.2023.108824
https://doi.org/10.1016/j.fcr.2023.108824
Optical satellite sensors cannot see the Earth's surface through clouds. Despite the periodic revisit cycle, image sequences acquired by Earth observation satellites are therefore irregularly sampled in time. State-of-the-art methods for crop classif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f5c79c162bada141c421a0aa64c0bed1
Autor:
Gregor Perich, Konrad Schindler, Constantin Streit, Stefano D'Aronco, Jan Dirk Wegner, Frank Liebisch, Mehmet Ozgur Turkoglu
Publikováno v:
Remote Sensing of Environment, 264
The aim of this paper is to map agricultural crops by classifying satellite image time series. Domain experts in agriculture work with crop type labels that are organised in a hierarchical tree structure, where coarse classes (like orchards) are subd
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97fcef4fdaca5a6739af55ac3e4df5e4
https://doi.org/10.1016/j.rse.2021.112603
https://doi.org/10.1016/j.rse.2021.112603
Publikováno v:
AAAI
ISSUE=33;TITLE=33rd AAAI Conference on Artificial Intelligence, AAAI 2019
Thirty-Third AAAI Conference on Artificial Intelligence, Thirty-First Conference on Innovative Applications of Artificial Intelligence, The Ninth Symposium on Educational Advances in Artificial Intelligence: AAAI-19, IAAI-19, EAAI-20 : January 27-February 1, 2019, Hilton Hawaiian Village, Honolulu, Hawaii, USA, 8901-8908
STARTPAGE=8901;ENDPAGE=8908;TITLE=Thirty-Third AAAI Conference on Artificial Intelligence, Thirty-First Conference on Innovative Applications of Artificial Intelligence, The Ninth Symposium on Educational Advances in Artificial Intelligence
ISSUE=33;TITLE=33rd AAAI Conference on Artificial Intelligence, AAAI 2019
Thirty-Third AAAI Conference on Artificial Intelligence, Thirty-First Conference on Innovative Applications of Artificial Intelligence, The Ninth Symposium on Educational Advances in Artificial Intelligence: AAAI-19, IAAI-19, EAAI-20 : January 27-February 1, 2019, Hilton Hawaiian Village, Honolulu, Hawaii, USA, 8901-8908
STARTPAGE=8901;ENDPAGE=8908;TITLE=Thirty-Third AAAI Conference on Artificial Intelligence, Thirty-First Conference on Innovative Applications of Artificial Intelligence, The Ninth Symposium on Educational Advances in Artificial Intelligence
The visual world we sense, interpret and interact everyday is a complex composition of interleaved physical entities. Therefore, it is a very challenging task to generate vivid scenes of similar complexity using computers. In this work, we present a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3b61d6cbbe600c900e51a36668934d33
http://arxiv.org/abs/1902.00671
http://arxiv.org/abs/1902.00671
We propose a new STAckable Recurrent cell (STAR) for recurrent neural networks (RNNs), which has fewer parameters than widely used LSTM and GRU while being more robust against vanishing or exploding gradients. Stacking recurrent units into deep archi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8bb877f3a0cbecd8f956676c3beaaea3
Publikováno v:
IROS
3D visual understanding of the surrounding environment is vital for successful mobile robotic tasks such as autonomous navigation or general object interaction. However, current systems have limited perceptual capabilities in the sense that they are
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dc7b7d73073449a96e810893e8687bb6
https://doi.org/10.1109/iros.2018.8593810
https://doi.org/10.1109/iros.2018.8593810
Autor:
Tugce Arican, Mehmet Ozgur Turkoglu
Publikováno v:
BIOSIG
Recent studies show that eyebrows can be used as a biometric or soft biometric for recognition. In some scenarios such as partially occluded or covered faces, they can be used for recognition. In this paper, we study eyebrow recognition using texture
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7547d6905b5b4a383741feebea493eb3
https://doi.org/10.23919/biosig.2017.8053522
https://doi.org/10.23919/biosig.2017.8053522