January Edition: Self-Driving Cars
10 Must-Read Articles
Understanding SSD MultiBox — Real-Time Object Detection In Deep Learning
By Eddie Forson — 11 min read.
Since AlexNet took the research world by storm at the 2012 ImageNet Large-Scale Visual Recognition Challenge (ILSVRC), deep learning has become the go-to method for image recognition tasks, far surpassing more traditional computer vision methods used in the literature.
Self Driving Cars, The Most Hyped Thing Since…The Segway?
By Michael Guo — 8 min read.
With headlines like these, it’s hard not to get excited about autonomy and self driving cars. After all, we’ve seen the cars in Minority Report, Total Recall, and iRobot, and thought to ourselves: “When can we finally get into thosecars?”
Vehicle Detection and Tracking
By Ivan Kazakov — 7 min read.
This is the Udacity’s Self-Driving Car Engineer Nanodegree Program final project for the 1st Term. Source code and a more technically elaborated writeup are available on GitHub
Lane Detection with Deep Learning
By Michael Virgo — 9 min read.
People can find lane lines on the road fairly easily, even in a wide variety of conditions. Unless there is snow covering the ground, extremely heavy rainfall, the road is very dirty or in disrepair, we can mostly tell where we are supposed to go, assuming the lines are actually marked.
Planning the path for a Self-Driving Car on a Highway
By Priya Dwivedi — 6 min read.
Path planning is the brain of a self driving car. It is the module that tries to replicate the thinking and decision making we humans do while driving — read the map, analyze our environment (other vehicles and pedestrians) and decide the optimal action based on safety, speed and traffic rules.
ConvNets Series. Spatial Transformer Networks
By Kirill Danilyuk — 11 min read.
Spatial transformer is yet another LEGO block in the collection of differentiable modules. It removes spatial invariance from images by applying a learnable affine transformation followed by interpolation.
Vehicle Detection and Tracking: Udacity’s Self-driving Car Nanodegree
By Dhanoop Karunakaran — 10 min read.
Vehicle detection and tracking is important in self-driving technologies to drive car safely. In this project, goal is to write a software pipeline to detect vehicles in a video.
How to Train your Self-Driving Car to Steer
By Norman Di Palo — 5 min read.
Neural networks, and particularly deep learning research, have obtained many breakthroughs recently in the field of computer vision and other important fields in computer science.
Robots Are Wrong Too — Confusion Mapping for the Worst Case
By Chris Butler — 8 min read.
When was the last time a calculator didn’t do what you wanted it to? When was the last time that a person did? Algorithms like machine learning are in between these two from a deterministic standpoint.
Building a Toy Detector with Tensorflow Object Detection API
By Priya Dwivedi — 5 min read.
This project is second phase of my popular project -Is Google Tensorflow Object Detection API the easiest way to implement image recognition? In the original article I used the models provided by Tensorflow to detect common objects in youtube videos.
We also thank all the great new writers who joined us recently, Chuong Do, Savina van der Straten, Marco Brambilla, Christopher Gill, Aravind Srinivasan, Max Lawnboy, Simeon Kostadinov, An Luong, Ethan Arsht, Danny Hernandez, Enrique Herreros, Daniel Boterhoven, Vitaly Davydov, Nahid Alam, Hamel Husain, kenta suzuki, Jennifer Marley, Ben Shaver, Boris Smus, Ellis Brown, Sagar Howal, Josh Yazman, Indra den Bakker, and many others. We invite you to take a look at their profiles and check out their work.
