Showing results for Cognitive Services - ISE Developer Blog

A synopsis of our key learnings and findings from using Semantic Kernel.

Potential semantic routing solution using Azure AI Search for scalable query handling.

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.

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.

This blog post proposes a methodology to disambiguate misspelled entities by comparing the search retrieval performance with different custom search analyzers in a search engine.

A scenario commonly encountered in public safety and justice is the need to collect and index digital data recovered from devices, so that investigating officers can perform evidence-based analysis. We recently built an advanced evidence analysis platform that uses Azure AI services for automated labelling of media and documents.

This code story describes CSE's work with ZenCity to create a data pipeline on Azure Databricks supported by a CI/CD pipeline on TravisCI. The aim of the collaboration was to create a pipeline capable of processing a stream of social posts, analyzing them, and identifying trends.

Golf performance tracking startup Arccos joined forces with Commercial Software Engineering (CSE) developers in hopes of unveiling new improvements to their "virtual caddie" this summer.

Extracting general concepts, rather than specific phrases, from documents and contracts is challenging. It's even more complicated when applied to scanned documents containing handwritten annotations. We describe using object detection and OCR with Azure ML Package for Computer Vision and Cognitive Services API.

When it comes to identifying and understanding influential voices in social media, context is key. See how we used topic detection, sentiment analysis, and Azure Functions to automate context-aware social media insights.