Preventing Rhino Poaching With Microsoft Azure
Peace Parks Foundation partnered with Microsoft to build a scalable alerting system that helps to fight rhino poaching in South Africa.
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Active Learning for Object Detection in Partnership with Conservation Metrics
CSE teamed up with Conservation Metrics to use Active Learning to allow for more efficient data labeling for object detection projects.
Satellite Images Segmentation and Sustainable Farming
Can Machine Learning help with detecting sustainable farming practices? In this blog post inspired by our collaboration with Land O’Lakes we share the lessons we learned in the image segmentation space.
Sequence Intent Classification Using Hierarchical Attention Networks
We analyze how Hierarchical Attention Neural Networks could be helpful with malware detection and classification scenarios, demonstrating the usefulness of this approach for generic sequence intent analysis. The novelty of our approach is in applying techniques that are used to discover structure in a narrative text to data that describes the behavior of executables.
Bird Detection with Azure ML Workbench
We demonstrate how to train Object Detection models using CNTK and Tensoflow DNN frameworks. Azure ML Workbench is used as the main training and model hosting infrastructure.
Learning Image to Image Translation with Generative Adversarial Networks
Microsoft has partnered with Getty Images to explore how Neural Nets could be used to transform the stock photo industry.
Food Classification with Custom Vision Service
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.
