pnnl/gumby-spectral-imaging
Deep Learning models for multi- and hyper-spectral imaging data
Engineering topics
Publications and source records attributed to Central, PNNL Developer.
Deep Learning models for multi- and hyper-spectral imaging data
The DEIMoS Graphical User Interface was created as an interface for DEIMoS: Data Extraction for Integrated Multidimensional Spectrometry. DEIMoS is a Python package to process data from mass spectrometry instrument developed at PNNL.
Commercial Parking Application is a web-based application that alerts delivery drivers in real time to available parking spaces near their destinations. Parking availability can be viewed on a map in real-time, using sensor data supplied by external services. The app can be viewed with a web browser on a mobile device or PC. Currently the app supports connections to real time sensors from Lacuna, Fybr, Cleverciti, and Automotus
PTM-Psi is a Python 3 package that combines several capabilities to streamline the workflow to interrogate the impact of PTMs on proteins using well-established software packages. The workflow of the PTM-Psi software package includes input files and launch instances from standard packages such as AlphaFold, NWChem, GROMACS, and the Autodock Suite
This research code base includes functions to compute statistics of image distributions in (spatial DFT) frequency space, train deep learning image classifiers on these distributions with variable depth and weight decay, and finally measure the sensitivity of the trained models to perturbations along (spatial DFT) frequency components.
A topology-based anomaly detection tool for temporal varying data. The input is json or CSV formatted data with a timestamp field identified. The algorithm computes vectorizations (using a vectorization config file) of time windows of data and computes a topological measure of anomalousness. The output is a sequence of anomaly scores for each time window