Python Vision-Based Driving CNN Development -- 2

I am seeking an advanced Python developer, proficient in machine learning and computer vision, to train a Convolutional Neural Network (CNN) aimed at vision-based driving.

Project Scope:

- Dataset: I didn't provide a specific dataset for this project. Therefore, the successful candidate should assist in identifying or creating an appropriate dataset. Your ability to guide the process of dataset selection/creation will be beneficial.

- Purpose: Contrary to the question being skipped, keep in mind that the CNN should be designed primarily for autonomous driving tasks such as object detection and lane keeping. Proficiency in training AI in these aspects will be a strength.

- Model Architecture: Unsure of the specific CNN model architecture, I need an expert who will either propose a fitting CNN architecture or help design a new custom one. A strong understanding of CNN architectures relevant to vision-based driving is highly desirable.

Please note, that applicants with successful track records in similar projects will be given precedence. Advanced knowledge of Python, Tensorflow, or PyTorch and AI strategies for autonomous driving are paramount skills for the job.

Let's enhance autonomous vehicle safety together!

The reference controller completes each level relatively efficiently: zengarden and lighthouse in under 50 sec, hacienda and snowtuxpeak in under 60 sec, cornfield_crossing and scotland in under 70 sec.

Note that these times are in-game times and will generally be less than the total computational runtime. Your controller/planner should complete each track within a certain amount of time (see grader for details). See less

I will share more details in PM.

thank you.