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[HTML][HTML] A review of optical methods for ultrasensitive detection and characterization of nanoparticles in liquid media with a focus on the wide field surface plasmon …
Abstract Development of nanotechnology and corresponding industries during the last
decade resulted in a new challenge for analytical science. This includes an ultrasensitive …
decade resulted in a new challenge for analytical science. This includes an ultrasensitive …
[HTML][HTML] Surface plasmon resonance (SPR)-based biosensors as instruments with high versatility and sensitivity
V Shpacovitch, R Hergenröder - Sensors, 2020 - mdpi.com
Surface plasmon resonance (SPR), as a physical phenomenon, is not restricted only to
events occurring in thin planar metal films. A broad spectrum of differently nanostructured …
events occurring in thin planar metal films. A broad spectrum of differently nanostructured …
Efficient realization of decision trees for real-time inference
KH Chen, C Su, C Hakert, S Buschjäger… - ACM Transactions on …, 2022 - dl.acm.org
For timing-sensitive edge applications, the demand for efficient lightweight machine learning
solutions has increased recently. Tree ensembles are among the state-of-the-art in many …
solutions has increased recently. Tree ensembles are among the state-of-the-art in many …
[HTML][HTML] A data-centric augmentation approach for disturbed sensor image segmentation
A Roth, K Wüstefeld, F Weichert - Journal of Imaging, 2021 - mdpi.com
In the context of sensor-based data analysis, the compensation of image artifacts is a
challenge. When the structures of interest are not clearly visible in an image, algorithms that …
challenge. When the structures of interest are not clearly visible in an image, algorithms that …
Register Your Forests: Decision Tree Ensemble Optimization by Explicit CPU Register Allocation
Bringing high-level machine learning models to efficient and well-suited machine
implementations often invokes a bunch of tools, eg~ code generators, compilers, and …
implementations often invokes a bunch of tools, eg~ code generators, compilers, and …
[ספר][B] Applications
K Morik, J Rahnenführer, C Wietfeld - 2022 - degruyter.com
Machine Learning under Resource Constraints addresses novel machine learning
algorithms that are challenged by high-throughput data, by high dimensions, or by complex …
algorithms that are challenged by high-throughput data, by high dimensions, or by complex …