2,136 research outputs found

    Blandsæd – Et aktiv mod det ekstreme vejr

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    Efter to usædvanlige vækstsæsoner – den ene kold og våd, den anden ekstremt varm og tør – er det virkelig blevet tydeligt, at metrologernes forudsigelser om mere ekstremt vejr i fremtiden kan holde stik. Dette sætter større krav til diversitet, fleksibilitet og robusthed i sædskiftet. Her har blandsæd en fordel

    Landmand kend din jord

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    Læs om hvordan du diagnosticerer din jord: Hvordan gør du? Hvad skal du kigge efter? Hvad kan gøres for at forbedre din jord

    Investigation and Modelling of Diesel Hydrotreating Reactions

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    Fokus på jordfrugtbarhed hos Nørby Grøntsager

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    Ole Nørby driver Nørby Grøntsager på Stevns. Gården er 24 ha og har været drevet økologisk siden år 2000. Her dyrkes 50 forskellige grøntsager, som sælges i egen gårdbutik, via en abonnementsordning og til enkelte lokale aftagere. Gårdbutikken står for 70% af grøntsagssalget og kunderne kommer hovedsageligt fra de nærliggende større byer som Køge

    Havresorter 2019

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    Anbefalinger: Til gryn og glutenfri gryn - Symphony og Seldon. Til foder –Poseidon, Delfin og Symphony

    Adult Education for Deaf People

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    Non

    Termination of cover crops with reduced tillage methods in organic agriculture

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    Studies were made with the ability of green manure plants to regrow after variable extent of mechanical damage, and variable depth of soil cover. The study showed highly significant differences in responses among the plants, differences which may be used for species choice as well as for defining optimal methods for termination in reduced tillage organic farming

    Aspects of User Experience in Augmented Reality

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    Autoencoding beyond pixels using a learned similarity metric

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    We present an autoencoder that leverages learned representations to better measure similarities in data space. By combining a variational autoencoder with a generative adversarial network we can use learned feature representations in the GAN discriminator as basis for the VAE reconstruction objective. Thereby, we replace element-wise errors with feature-wise errors to better capture the data distribution while offering invariance towards e.g. translation. We apply our method to images of faces and show that it outperforms VAEs with element-wise similarity measures in terms of visual fidelity. Moreover, we show that the method learns an embedding in which high-level abstract visual features (e.g. wearing glasses) can be modified using simple arithmetic
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