FLOKI Studio

FLOKI Studio

nader rahman

nader rahman


user-friendly interface for children to enhance their potential

Modern Code, Internet of Things

  • 2 Collaborators




Folki IDE will provide a user-friendly interface for children to enhance their potential . In this interface we will find a lot of scenarios , in which the user will face daily real problems , and learn to solve them using the IOT . With this scenarios , he will be able to build his own IOT solution , learn repeat loops , conditionals , basic algorithms , manipulate the sensors with different actions. Mainly , Students drag and connect the ‘Blocks’ which are basically pre-programmed pieces of code. Once you think you’ve planned out the program , connect the board and sensors correctly; you press ‘Run’, and the board will execute your program.

The great thing about Folki IDE is that it’s largely self-directed. Teachers and parents can organize and plan the events in school, with only a small amount of prep for teachers, e.g. choosing the Tutorials. But once the kids have been brought together in the classroom, they (and the tutorials) do the rest.



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Phil C. updated status

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Phil Carlisle

I'm a researcher who's PhD is in the area of Digital Actors (mainly for videogames/interactive storytelling). So I'm looking at technology that will help drive advances in Digital Actor behavior and production.

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Filip C. updated status

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Filip Ceglik


My name is Filip and I recently started my amazing adventure with artificial intelligence and I am loving it! I have lots of ideas for making life easier or at least more amazing and breathtaking. My main goals are to make AI's for medical purposes like identifying tumors, etc. Automated self driving cars, face identification and more. Also I am hobbyist game developer and in this area, there are lots of things to push AI into. At the moment I am working on a program which can identify a brain tumors from MRI's photos. I am super excited for working in AI area and hope that I am going to achieve these goals.

Have a nice day guys and I wish you good luck with your projects.

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Gunasekaran S. updated status

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Gunasekaran Sengodan

I'm learning and trying to develop my own idea to solve lot of real world problems existing in IOT space(This may be for a Person, Business, NGO etc...). I'm looking to aware what best practices available already to share up my idea and collaborate like minded engineers to discuss various ideas to brings it next level as every day progress.

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Yash A. created project Game development frameworks and Tensorflow

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Game development frameworks and Tensorflow

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.

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donel a. updated status

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donel adams

Google or Bing name to view associate networks fostering business development by maximizing any platform potential for growth utilizing AI

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Justin L. created project SPIDER-MAN: HOMECOMING - Virtual Reality Experience

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SPIDER-MAN: HOMECOMING - Virtual Reality Experience

Sony Pictures Virtual Reality announced a new VR experience for Columbia Pictures’  upcoming “Spider-Man: Homecoming” flick Friday that will let players experience how it feels like to be Spidey. They’ll be able to do some target practice with Spider-Man’s new web shooters, and sling themselves through the air to face off against Spider-Man’s arch-nemesis, The Vulture. The experience will be available for free across all major VR platforms, including PlayStation VR, Oculus Rift and HTC Vive on June 30, a week before the movie is scheduled to hit theaters.

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Suraj R. created project Vehicle Detection

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Vehicle Detection

Detecting vehicles in a video stream is an object detection problem. An object detection problem can be approached as either a classification problem or a regression problem. In the classification approach, the image are divided into small patches, each of which will be run through a classifier to determine whether there are objects in the patch. The bounding boxes will be assigned to patches with positive classification results. In the regression approach, the whole image will be run through a convolutional neural network directly to generate one or more bounding boxes for objects in the images.

The goal of this project is to detect the vehicles in a camera video. The You Only Look Once (YOLO) algorithm is used here to detect the vehicles from a dash camera video stream. This feature is an extremely important breakthrough for self-driving cars as we can train the model to also recognize birds, people, stop signs, signals and much more.

In this project, we will implement the version 1 of tiny-YOLO in Keras, since it’s easy to implement and is reasonably fast.

The YOLO approach of the object detection is consists of two parts: the neural network part that predicts a vector from an image, and the postprocessing part that interpolates the vector as boxes coordinates and class probabilities. For the neural network, the tiny YOLO v1 is consist of 9 convolution layers and 3 full connected layers. Each convolution layer consists of convolution, leaky relu and max pooling operations. The output of this network is a 1470 vector, which contains the information for the predicted bounding boxes. The 1470 vector output is divided into three parts, giving the probability, confidence and box coordinates.

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