dam-anomaly-detection
[AVSS21 Oral] A framework consisting of Dissimilarity Attention Module (DAM) to discriminate the anomaly instances from normal ones both at feature level and score level. In order to decide instances to be normal or anomaly, DAM takes local spatio-temporal (i.e. clips within a video) dissimilarities into account rather than the global temporal context of a video.
https://github.com/blue-yonder/grammar-of-graphics-minard-example
Recreation of Charles Minard's Data Visualisation in Python using Altair
https://github.com/blue-yonder/di-csv2xml
di-csv2xml - a command line tool for converting CSV to Blue Yonder Supply & Demand API compatible XML
multichannelqrsdetector
Code of the paper Optimal data fusion for the improvement of QRS complex detection in multi-channel ECG recordings
auto_populate_fields
This REDCap Module provides rich control of default values for data entry fields via a set of action tags. These action tags allow fields to be populated based on values from an ordered list of fields and static values. The fields can be read from the current event or the previous event in longitudinal projects.
