Game development frameworks and Tensorflow

Game development frameworks and Tensorflow

Yash Akhauri

Yash Akhauri

Jhunjhunu, Rajasthan

While training a neural network, you might be limited by your computer's resources, this project aims to circumvent that.

Game Development, Artificial Intelligence


This project aims to create a way to enable communication between two frameworks. Such as allowing a simulation in say Unity, to continuously send packets of data, that can be used by another computer in the local network to learn, or make inferences and return a suitable response. This can be useful for computationally expensive tasks, where both the simulation and the neural network are typically huge. In the link, you will see a blog indicating a rudimentary implementation of a local server client connection which has a simple neural network.

Looking for collaboration to improve the speed, and alternate methods to do this in a local network or even over the internet.


Socket programming and deep learning

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Anthony C. created project gRPC framework to support application to utilize the Cache Allocation Technology of Intel's RDT

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gRPC framework to support application to utilize the Cache Allocation Technology of Intel's RDT

Network Functions Virtualization ( NFV ) and Service Function Chaining ( SFC ) have moved from idea to POC to implementation stage . The challenge still remains to get bare metal performance from virtual machines . Resource Director Technology (RDT) from Intel is designed to bring in QoS to the virtual machine resources. gRPC from Google is a framework which could be used to design priority based services . This project integrates these technologies and creates a framework for more reliable and efficient services via gRPC enhanced with RDT.

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Ravi K. updated status

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Ravi K

Hi, I am very eager to learn AI technologies, I am master student at Governors State University,Chicago.

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Timothy P. created project MR. Configurator Tool

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MR. Configurator Tool

This tool was designed to speed up calibration of your MR setup. This article explains how to use the tool and help you get the most out of your MR experiences. For VR users and streamers, making MR videos is a great way to show a different perspective to people who aren’t wearing a head-mounted display (HMD), while for VR developers, MR videos are a great way to create trailers and show a more comprehensive view of the VR experience.

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Basavaraj H. created project Apparent/Real Image Estimation using Deep Learning

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Apparent/Real Image Estimation using Deep Learning

IMDB-WIKI age dataset processing and data loading into PyTorch model Fine tune VGG16 pre-trained on ImageNet using IMDB-WIKI database to estimate real age Train the fine-tuned model using LAP database to estimate apparent age Real age estimation is evaluated using MAE Used Ensemble 8 VGG16 nets to estimate the apparent age

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Makiko K. created project Smarter Wireless Power Transfer Technology

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Smarter Wireless Power Transfer Technology

Wireless Power Transfer Technology enables people charging devices without a physical connection to the battery source. There are two main methods: Magnetic Inductance and Magnetic Resonance.

Magnetic Inductance charges devices within proximity. Magnetic Resonance, in turn, can charge further.

This project is an early proposal to evaluate how the different possible variables can impact the efficiency of the system, i.e., how fast can the device be charged subject to the distance, for example, material, object collision, room temperature, etc impact on the efficiency of the device.

Subject to these variables, the AI component of this project seeks to create a "smart wireless power charger", which reading through sensors the various conditions of the environment suggest the optimal distance for energy charging and placement without compromising the comfort of the user.

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Aashiq J. updated status

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Bob D. added a comment on project AI Skin Cancer Detection

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AI Skin Cancer Detection

Between 40 and 50 percent of Americans who live to age 65 will have either basal cell carcinoma or squamous cell carcinoma at least once.

The annual cost of treating skin cancers in the U.S. is estimated at $8.1 billion: about $4.8 billion for nonmelanoma skin cancers and $3.3 billion for melanoma.

An estimated 9,730 people will die of melanoma in 2017.

The estimated 5-year survival rate for patients whose melanoma is detected early is about 98 percent in the U.S. The survival rate falls to 62 percent when the disease reaches the lymph nodes, and 18 percent when the disease metastasizes to distant organs

Our project plans to train and classify skin cancer types so that user can try to detect cancer in the real time. When detected with high confidence score, user will be given suggestion to see dermatologist for effective treatments.

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Bob Duffy

Folsom, CA, USA