Titlebook: Waldschutz und Umwelt; Joachim Reisch Book 1974 Springer-Verlag Berlin Heidelberg 1974 Biologische Schädlingsbekämpfung.Forstschutz.Forsts

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es in the development process, which has raised the threshold for users to learn and appreciate calligraphy. With the development of deep learning technology, deep feature extraction technology based on convolutional neural network has made important breakthroughs in the task of calligraphy Chinese

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port to stop smoking when pregnant is likely to increase their motivation to quit. We aim to combine 3D modelling and physiological simulations to create a science-based educational tool for pregnant women. We employ parametric mesh (linear Lagrange or cubic Hermite) in the OpenCMISS-Zinc package to

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Joachim Reischeveral interaction devices have to be tracked simultaneously. While the geometry of all devices and the spatial layout of visual landmarks on the devices are well known, problems of occlusion as well as of prohibitively large search spaces remain to be solved. The main contribution of the paper is i

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Joachim Reischstream tasks. Unfortunately, existing methods require massive amounts of computing power with large batch sizes and batch norm statistics synchronized across multiple GPUs. This effectively excludes substantial parts of the computer vision community from the benefits of self-supervised learning who

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Joachim ReischISR methods tend to estimate HR image by edge-preserving constraint. In this paper, a novel learning based SISR method is proposed to reconstruct HR image by using joint HR gradient field and high frequency constraint. In the training phase, interpolated training LR patches with similar structure ar

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eatures are extracted independently of the task in hand, these features tend to change their representations in favor of different hypotheses to find the best possible representation. The features introduced in this paper take advantage of the part-based models at the feature level by combining the

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