We address the challenge of creating a custom search experience for a specific domain area. We also provide a guide for creating your own custom search experience by leveraging Azure Search and Cognitive Services and sharing custom code for iterative testing, measurement and indexer redeployment.
An overview of different image classification approaches including Microsoft Azure Custom Vision Service and CNTK for various levels of classification complexity.
Claiming expenses is usually a manual process. This project aims to improve the efficiency of receipt processing by looking into ways to automate this process. This code story describes how we created a skeletal framework to achieve the following: We found a few challenges in addressing these goals. For instance, the quality of...
We collaborated on an image classification pipeline to perform automatic face detection and matching using machine learning via Microsoft Cognitive Services Face API. Our project was built with Azure Functions to process images using message queues.
We use IoT sensors to collect positional and motion data from professional and amateur skiers to classify expertise and skill level through machine learning.
Microsoft has partnered with Getty Images to explore how Neural Nets could be used to transform the stock photo industry.
How we created an app to identify foods and their nutritional content by using the new Custom Vision Service to leverage domain-specific image recognition powered by DNNs.
We use Deep Learning to turn a painful and time-consuming leak-detection task for water and oil pipelines into a fast, painless process. Using Python and Fast Fourier Transforms, we turn audio sensor data into images, then use Convolutional Neural Networks to detect and classify pipeline anomalies.
Creating an object detection model using Microsoft's open source deep learning framework CNTK and its implementation of Fast-RCNN.
Building a video tagging tool on top of CNTK to enable developers to create, review and iterate object detection models.
