CSE Developer Blog

Detecting “Action” and “Cut” in Archival Footage Using a Multi-model Computer Vision and Audio Approach with Azure Cognitive Services

Movies and TV shows require multiple takes per scene and may have a substantial amount of archival footage as a result. Here, we use Azure Cognitive Services and custom code to develop a multi-model Machine Learning (ML) solution to automatically detect discardable footage to save media companies manual archiving hours and storage space.

Building an Action Detection Scoring Pipeline for Digital Dailies

Media companies capture footage filmed for the entire day in what's known as ‘digital dailies’. When talking about terabytes and petabytes of content, storage costs can be a factor. Lets explore Machine Learning approaches to identify which content can be archived or discarded which will save on those storage costs.

Building A Clinical Data Drift Monitoring System With Azure DevOps, Azure Databricks, And MLflow

Hospitals around the world regularly work towards improving the health of their patients as well as ensuring there are enough resources available for patients awaiting care. During these unprecedented times with the COVID-19 pandemic, Intensive Care Units are having to make difficult decisions at a greater frequency to optimize patient health ...

Preventing Rhino Poaching With Microsoft Azure

In the last eight years, poaching in Africa has been happening at an alarming rate. Currently, the continent loses three rhinos a day. As part of our team’s mission to find new ways that technology can positively impact our world, we’ve been collaborating with the Combating Wildlife Crime team Peace Parks Foundation (PPF), in partnership with