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An analysis review of detection coronavirus disease 2019 (COVID-19) based on biosensor application
Timely detection and diagnosis are essentially needed to guide outbreak measures and
infection control. It is vital to improve healthcare quality in public places, markets, schools …
infection control. It is vital to improve healthcare quality in public places, markets, schools …
[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 …
Deep learning detection of nanoparticles and multiple object tracking of their dynamic evolution during in situ ETEM studies
In situ transmission electron microscopy (TEM) studies of dynamic events produce large
quantities of data especially under the form of images. In the important case of …
quantities of data especially under the form of images. In the important case of …
The Employment of the Surface Plasmon Resonance (SPR) Microscopy Sensor for the Detection of Individual Extracellular Vesicles and Non-Biological Nanoparticles
A wide-field surface plasmon resonance (SPR) microscopy sensor employs the surface
plasmon resonance phenomenon to detect individual biological and non-biological …
plasmon resonance phenomenon to detect individual biological and non-biological …
Develo** surface plasmon resonance imaging for discrete particle detection based on a silver layer coated with polyacrylic acid/iodine polyelectrolyte brushes
The detection and analysis of low concentrations of chemical and biological particles
presents an enduring challenge in scientific exploration. Among the various techniques …
presents an enduring challenge in scientific exploration. Among the various techniques …
Timing isolation and improved scheduling of deep neural networks for real‐time systems
In recent years, the performance of deep neural networks (DNNs) is significantly improved,
making them suitable for many application fields, such as autonomous driving, advanced …
making them suitable for many application fields, such as autonomous driving, advanced …
[HTML][HTML] A data-centric augmentation approach for disturbed sensor image segmentation
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 …
[HTML][HTML] Nanoparticle classification using frequency domain analysis on resource-limited platforms
A mobile system that can detect viruses in real time is urgently needed, due to the
combination of virus emergence and evolution with increasing global travel and transport. A …
combination of virus emergence and evolution with increasing global travel and transport. A …
Adaptive quality optimization of computer vision tasks in resource-constrained devices using edge computing
This paper presents an approach to optimize the quality of computer vision tasks in resource-
constrained devices by using different execution versions of the same task. The execution …
constrained devices by using different execution versions of the same task. The execution …
[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 …