27 citations · 55 across the 11 of their papers we have counts for
11 papers
Explainable Self-Organizing Artificial Intelligence Captures Landscape Changes Correlated with Human Impact Data
John M. Wandeto, Birgitta Dresp-Langley
Novel methods of analysis are needed to help advance our understanding of the intricate interplay between landscape changes, population dynamics, and sustainable development. Self…
Spatiotemporal modeling of grip forces captures proficiency in manual robot control
Rongrong Liu, John M. Wandeto, Florent Nageotte +3
This paper builds on our previous work by exploiting Artificial Intelligence to predict individual grip force variability in manual robot control. Grip forces were recorded from va…
Surgical task expertise detected by a self-organizing neural network map
Birgitta Dresp-Langley, Rongrong Liu, John M. Wandeto
Individual grip force profiling of bimanual simulator task performance of experts and novices using a robotic control device designed for endoscopic surgery permits defining benchm…
Human Symmetry Uncertainty Detected by a Self-Organizing Neural Network Map
Birgitta Dresp-Langley, John M. Wandeto
Symmetry in biological and physical systems is a product of self organization driven by evolutionary processes, or mechanical systems under constraints. Symmetry based feature extr…
Pixel precise unsupervised detection of viral particle proliferation in cellular imaging data
Birgitta Dresp-Langley, John M. Wandeto
Cellular and molecular imaging techniques and models have been developed to characterize single stages of viral proliferation after focal infection of cells in vitro. The fast and…
The quantization error in a Self-Organizing Map as a contrast and colour specific indicator of single-pixel change in large random patterns
John M Wandeto, Birgitta Dresp-Langley
The quantization error in a fixed-size Self-Organizing Map (SOM) with unsupervised winner-take-all learning has previously been used successfully to detect, in minimal computation…
Detection of small changes in medical and random-dot images comparing self-organizing map performance to human detection
John Wandeto, Henry Nyongesa, Yves Remond +1
Radiologists use time series of medical images to monitor the progression of a patient condition. They compare information gleaned from sequences of images to gain insight on progr…
Unsupervised automatic classification of Scanning Electron Microscopy (SEM) images of CD4+ cells with varying extent of HIV virion infection
John M. Wandeto, Birgitta Dresp-Langley
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 e…
Detection of Structural Change in Geographic Regions of Interest by Self Organized Mapping: Las Vegas City and Lake Mead across the Years
John M. Wandeto, Henry O. Nyongesa, Birgitta Dresp-Langley
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 citi…
Using the quantization error from Self-Organized Map (SOM) output for detecting critical variability in large bodies of image time series in less than a minute
Birgitta Dresp-Langley, John Mwangi Wandeto
The quantization error (QE) from SOM applied on time series of spatial contrast images with variable relative amount of white and dark pixel contents, as in monochromatic medical i…
On the detectability by novices, radiologists, and computer algorithms of smallest increases in local single dot size in random-dot images
Birgitta Dresp-Langley, John Wandeto
Time-series of images may reveal important information about changes in medical or environmental conditions, depending on context. Visual inspection of images by humans (experts or…