We introduce a lightweight framework for semantic segmentation that utilizes structured classifiers as an alternative to deep learning methods. Biomedical data is known for being scarce and difficult to label. However...
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Optimal operating conditions for a process plant are typically obtained via model-based optimization. However, due to modeling errors, the operating conditions found are often sub-optimal or, worse, they can violate c...
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This study uses 125 responses from companies of all sizes predominantly headquartered in Germany, Switzerland, France and UK to reveal perceptions of the drivers of organisational agility. It further investigates curr...
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A large proportion of today's modern implantable medical devices (IMDs) comprises a wireless interface that enables the IMD to connect to another implanted device or a base station situated outside the body. Due t...
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3D cell culture models are important tools for the development and testing of new therapeutics. In combination with immunoassays and 3D confocal microscopy, crucial information like morphological or metabolic changes ...
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In this paper, we focus on a real world scenario of energy management of a smart-home. External signals, reflecting the low voltage grid's state, are used to address the challenge of balancing energy demand and ge...
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Knowledge transfer is one of the most critical success factors in IT offshore outsourcing projects and in many cases extremely underestimated. Compared to in-house or onsite projects, a much higher complexity appears ...
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Design of a novel varifocal freeform optics with aspheric surface profiles to reduce aberration effects. Its focal length will be tuned by rotating one of two helically formed lens bodies around the optical axis. ...
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Deep learning is often used for automated diagnosis support in biomedical image processing scenarios. Annotated datasets are essential for the supervised training of deep neural networks. The problem of consistent and...
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Supervised Neural Networks are used for segmentation in many biological and biomedical applications. To omit the time-consuming and tiring process of manual labeling, unsupervised Generative Adversarial Networks (GANs...
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