Developer Mesh: Editor’s Picks February 2018

Every month I pick out a few projects from Developer Mesh that I find interesting and share them with you. There is a diverse array of projects on the site, so narrowing it down to just five can be difficult! I hope you’ll take a few minutes to find out why each of these projects caught my eye and then hop over to mesh to see what other projects interest you.

Killing Zombies with Friends VR

Using an old-school format of taking turns sharing a virtual reality (V)R headset Killing Zombies with Friends lets you compete against your friends against the clock to find out who has the better sleight of hand in this local multiplayer game. Innovator Pablo Farias Navarro just released this on Steam and is looking for feedback, do you have what it takes to be the best in this apocalyptic world.

WRENCH: Workflow Management System Simulation Workbench

WRENCH enables a novel approach for scientific workflows making it possible to simulate large-scale hypothetical scenarios quickly and accurately on a single computer. By removing the need for expensive and time-consuming trial and error experiments, Student ambassador Ryan Tanaka’s software framework lets scientists can make quick and informed choices when executing their workflows.

Automatic Attendance Management System Using Face Detection

Student Ambassador Aravindhan wants to use facial recognition to replace manual attendance taking with an automatic attendance management system. Using a neural network consisting of 20 neurons in the hidden layer help to diagnose the pixels of the image and compare the results with the trained dataset allowing staff to use their own mobile device to register attendance for their class via their college network.

TASS Trainer

Innovator Adam Milton-Barker has built several versions of TASS computer vision projects over the years and this latest version replicates the transfer learning side of the original platform and is trained on Intel’s® AI Devcloud. In this project he walks you through building and training a convolutional neural network that can identify Darth Vader and Yoda.

Intelligent Security System for Abandoned Luggage

By using computer vision and machine learning Damla Gul Altunay aims to find abandoned luggage. Differing from existing studies by using projection, the application uses background modeling as a pre-process operation for the coming frame. If the static object is determined to be luggage then the event around the luggage and its owner will be analyzed based on the conditions around them.

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If you want to know more about Developer Mesh or the Intel® Software Innovator Program, contact Wendy Boswell.

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