Titlebook: Soil Engineering; Athanasios P. Dedousis,Thomas Bartzanas Book 2010 Springer-Verlag Berlin Heidelberg 2010 Agriculture.Agrochemicals.Recyc

ADJ

Johan Arvidsson,Thomas Kellerles with decoupled illumination and detection paths. Although the selective excitation scheme of such a microscope provides intrinsic optical sectioning that minimizes out-of-focus fluorescence background and sample photodamage, it is prone to light absorption and scattering effects, which results i

commonsense

aggressor

hypotension

Thomas Keller,Johan Arvidsson rates and timely treatment of colon cancer at an early stage. Even though there are deep learning methods developed for this task, variability in polyp size can impact model training, thereby limiting it to the size attribute of the majority of samples in the training dataset that may provide sub-o

Jacket

Forehead-Lift

S. Fountas,T. A. Gemtos,S. Blackmoremask annotations, existing polyp segmentation methods suffer from severe data shortage and impaired model generalization. Reversely, coarse polyp bounding box annotations are more accessible. Thus, in this paper, we propose a boosted . model to make full use of both accurate mask and extra coarse bo

Chronological

Dirk Ansorge,Richard John Godwindal (CC) and mediolateral-oblique (MLO) views. These multiple related images provide complementary diagnostic information and can improve the radiologist’s classification accuracy. Unfortunately, most existing deep learning systems, trained with globally-labelled images, lack the ability to jointly

真

Rupert Geischeder,Markus Demmel,Robert Brandhuberrapy implementation. Because of time and machine constraints, it involves imaging of different modalities, resolutions and dimensions, along with severe out-of-plane deformations to handle. In this paper, we introduce MSV-RegSyn-Net, a novel, scalable, deep learning-based framework for concurrent sl

Nibble

G. D. Vermeulen,J. N. Tullberg,W. C. T. Chamennnotations is crucial for unbiased comparisons because registration algorithms are trained and tested using these landmarks. Even though some data providers claim to have mitigated the inter-observer variability by having multiple raters, quality control such as a third-party screening can still be

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