12 PROJECTS THAT HELPS YOU BECOMING SELF-DRIVING CAR ENGINEER (PYTHON and C++ CODE AVALIABLE)

1. Finding Lane Lines on the Road
Github : https://lnkd.in/f9X4kS8

2. Traffic Sign Classification
https://lnkd.in/fj64DHM

3. Behavioral Cloning
https://lnkd.in/fw4mzfQ

4. Advanced Lane Finding
https://lnkd.in/fi8TPnc

5. Vehicle Detection
https://lnkd.in/f9yD3e3

6. Extended Kalman Filter
https://lnkd.in/f_53muK

7. Unscented Kalman Filter
https://lnkd.in/fxaZc-T

8. Kidnapped Vehicle
https://lnkd.in/fGKRjZz

9. Proportional–Integral–Derivative controller
https://lnkd.in/fEjPHpD

10. Model predictive control
https://lnkd.in/fnJwGkw

11. Path Planning
https://lnkd.in/fEe3NZA

12. Road Segmentation
https://lnkd.in/faVQcmm

#technology #artificialintelligence #selfdrivingcars

✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv

It seems like controversial papers or talks in the press about AI being unfair, incomplete or biased is fashionable these days.

We came across this paper which suggests that #selfdrivingcars are more likely to hit a black or dark skinned person.

Here is the paper “Predictive inequality in Object Detection”: https://lnkd.in/ebHbP6f

What do you think?

Are algorithms biased / trained on insufficient data? What can be done to solve this problem?
Photo credit: https://lnkd.in/eEqS39J
#algorithms #deeplearning #ai

✴️ @AI_Python_EN

Fast Estimating Pedestrian Moving State Based on Single 2D Body Pose by Shallow Neural Network.

Crossing or Not-Crossing (C/NC) problem is important to autonomous vehicles (AVs) to safely interact with pedestrians.

However, this problem setup ignores pedestrians walking along the direction of vehicles' movement (LONG).

To enhance AVs' awareness of pedestrians behavior, authors make the first step towards extending C/NC to C/NC/LONG problem and recognize them based on single body pose.

Paper: https://lnkd.in/dU8SinE
GitHub Code & JAAD dataset coming soon

#sensors #selfdrivingcars #autonomousvehicles #deeplearning

✴️ @AI_Python_EN