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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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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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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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Alexander H. updated status

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Alexander Holman

An AI you can have a conversation with. A routing engine for Taxi companies. A new C based programming language (to learn). Lots and lots of websites and apps.

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Projects (39)

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Jad Fayad

39 Rue Volta, 75003 Paris, France

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Bengaluru, Karnataka, India

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Surendra Naraga

Student at AP IIIT RK Valley, Rajiv Gandhi University of Knowledge Technologies and Intern at Intel

Bengaluru, Karnataka, India

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Jintu Das

Near Doul Gobinda Road, Amingaon, North Guwahati, Guwahati, Assam 781039, India

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Jean Lapaix

Fort Lauderdale, FL, USA

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Roberto Diaz Morales

I am currently the leader of the Data Science research line at Treelogic where I take part in many European H2020 research projects. My research interest include large scale Machine Learning, Parallelization and Deep Learning techniques. I obtained my PhD and Master Degree from the University Carlos III in Madrid where I worked under the supervision of Ángel Navia Vázquez. My Ph.D. research consisted in the parallelization of kernel methods, a family of of Machine Learning algorithms like Support Vector Machines (SVMs) or Gaussian Processes (GPs).

Madrid, España

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Gokula Krishnan Santhanam

Masters student @ ETH Zurich, Deep Learning Researcher working on both fundamentals and applications of Deep Learning technologies.

Limmatquai 122, 8001 Zürich, Switzerland

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Mate Kisantal

Machine Learning oriented Aerospace Control Engineering student, with some experience in self-driving car control design.

Rotterdam, Netherlands

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Rainbow

Thumb rupam Rupam Das

Created: 11/18/2015

Rainbow helps your kid to be smarter and ahead of the other kids and time with it's intuitive and...

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Meat Sense

Thumb wa5dhibh Erik Medina

Created: 02/15/2016

Meat Sense is an IoT oven designed to showcase natural voice interactions with an IoT device.

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Blynk

Thumb u3nm 7ef Pavel Bayborodin

Created: 01/15/2016

Build a mobile app for your connected project or product in less than 5 minutes

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ReconBot3000

Thumb qgk3r0ui Joyce Rigelo

Created: 11/06/2016

With the superpowers of the Intel Joule and the RealSense Camera, ReconBot3000 patrols your home ...

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Stellar

Thumb p7vgkosn Eskil Steenberg

Created: 04/04/2017

Stellar is a software platform for controlling elaborate LED lighting setups.

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G Prime

Thumb 12249946 10154463087553747 6687997361483543393 n Chris Skaggs

Created: 12/15/2015

A Unity game utilizing deterministic physics to simulate complex and moving gravity fields.

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