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Found 6 papers, 1 papers with code
Spatiotemporal modeling of grip forces captures proficiency in manual robot control
This paper builds on our previous work by exploiting Artificial Intelligence to predict individual grip force variability in manual robot control.
Surgical task expertise detected by a self-organizing neural network map
Individual grip force profiling of bimanual simulator task performance of experts and novices using a robotic control device designed for endoscopic surgery permits defining benchmark criteria that tell true expert task skills from the skills of novices or trainee surgeons.
Human Symmetry Uncertainty Detected by a Self-Organizing Neural Network Map
To this end, we exploit a neural network metric in the output of a biologically inspired Self Organizing Map, the Quantization Error (SOM QE).
Pixel precise unsupervised detection of viral particle proliferation in cellular imaging data
Cellular and molecular imaging techniques and models have been developed to characterize single stages of viral proliferation after focal infection of cells in vitro.
Unsupervised automatic classification of Scanning Electron Microscopy (SEM) images of CD4+ cells with varying extent of HIV virion infection
Archiving large sets of medical or cell images in digital libraries may require ordering randomly scattered sets of image data according to specific criteria, such as the spatial extent of a specific local color or contrast content that reveals different meaningful states of a physiological structure, tissue, or cell in a certain order, indicating progression or recession of a pathology, or the progressive response of a cell structure to treatment.
Detection of Structural Change in Geographic Regions of Interest by Self Organized Mapping: Las Vegas City and Lake Mead across the Years
Time-series of satellite images may reveal important data about changes in environmental conditions and natural or urban landscape structures that are of potential interest to citizens, historians, or policymakers.
