Machine Learning

Neural Network Performance

November 29, 2015 Nov 29, 2015 11/29/15

CY Yam

In this code story, we explore how the topology of a deep neural network can affect the performance of a text-based classifier.

Emotion Detection and Recognition from Text Using Deep Learning

November 29, 2015 Nov 29, 2015 11/29/15

CY Yam

Utilising deep learning to detect emotions from short, informal English text.

Data preparation: The Balancing Act

November 29, 2015 Nov 29, 2015 11/29/15

CY Yam

In this code story, we consider how data preparation can impact the performance of a classifier, and how that may lead to a refinement of problem statement, i.e. the important question we are asking.

Image Management in ASP.Net Using Azure Blob Storage

September 14, 2015 Sep 14, 2015 09/14/15

Michael Lanzetta

Uploading images to ASP.Net WebAPI, pre-processing, and storing in Azure Blob Storage without ever using the filesystem.

Using camera stream for real time object tracking in Windows apps

July 21, 2015 Jul 21, 2015 07/21/15

Petro Soininen

Findings from a pilot project where we identified reusable patterns, and ways to avoid common pitfalls when implementing object detection and tracking in Windows apps.

Turning Images into Entities Using Project Oxford

July 21, 2015 Jul 21, 2015 07/21/15

Michael Lanzetta

In this post, you'll see how we helped a startup to extract structured data from images - using Project Oxford's image recognition.

Communicating with Man’s Best Friend, Part I – Dog Tracking

July 21, 2015 Jul 21, 2015 07/21/15

Anthony Turner

With the arrival of commodity depth-capable cameras, specifically, the Microsoft Kinect, as well as high-performance machine learning algorithms, entirely new capabilities are made possible. Working with academic experts and others, we are attempting to track the movements, body language, and vocalizations of dogs.

Background and floor removal from depth camera data

July 21, 2015 Jul 21, 2015 07/21/15

Petro Soininen

Computer vision is used in various industries to process camera data as part of an analytics pipeline. This post introduces a reusable pattern and set of algorithms for extracting objects of interest from depth camera data.

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