Tag: Udacity

GitHub – balancap/SDC-Vehicle-Detection: Udacity Project

The goad of this project is to implement a robust pipeline capable of detecting moving vehicles in real-time. Even though the project was designed for using classic Computer Vision techniques, namely HOG features and SVM classifier, in agreement the course organizers, I decided like a few other students to go for a deep learning approach.

Several important papers on object detection using deep convolutional networks have been published the last few years. More specifically, Faster R-CNN, YOLO and Single Shot MultiBox Detector are the present state-of-the-art in using CNN for real-time object detection.

Even though there are a few differences between the three previous approaches, they share the same general pipeline. Namely, the detection network is designed based on the following rules:

  • Use a deep convolutional network trained on ImageNet as a multi-scale source of features. Typically, VGG, ResNet or Inception;
  • Provide a collection of pre-defined anchors boxes tiling the
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udacity/self-driving-car: The Udacity open source self-driving car project

Self-Driving Car

We’re Building an Open Source Self-Driving Car

And we want your help!

At Udacity, we believe in democratizing education. How can we provide opportunity to everyone on the planet? We also believe in teaching really amazing and useful subject matter. When we decided to build the Self-Driving Car Nanodegree program, to teach the world to build autonomous vehicles, we instantly knew we had to tackle our own self-driving car too.

Together with Google Self-Driving Car founder and Udacity President Sebastian Thrun, we formed our core Self-Driving Car Team. One of the first decisions we made? Open source code, written by hundreds of students from across the globe!

You can read more about our plans for this project.

Contributions

Here’s a list of the projects we’ve open sourced:

How to Contribute

Like any open source project, this code base will require a certain amount of thoughtfulness. However, when you add a

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