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Computer Vision and Perception for Self-Driving Cars (Deep Learning Course)

Learners: 230,854

Instructor: freeCodeCamp.org

Duration:

Get a comprehesive understanding of Computer Vision and Perception for Self-Driving Cars (Deep Learning Course). This is a free course from Youtube. OeClass provides this course data for free. Learn more certificate and details here. Discover the fascinating world of Computer Vision and Perception for Self-Driving Cars in this deep learning course. Join Robotics with Sakshay as they delve into the tasks required for a Self-Driving Car Perception unit. From road segmentation to object detection and 3D data visualization, this course covers it all. With comprehensive course contents and helpful links, you'll gain valuable insights into the cutting-edge technologies used in the field. Don't miss out on this opportunity to enhance your knowledge and skills in the exciting realm of self-driving cars. Enroll now and embark on a thrilling learning journey with Robotics with Sakshay.▼▲

Course Feature Course Overview Course Provider

Go to class

Course Feature

Cost:

Free

Provider:

Youtube

Certificate:

No Information

Language:

English

Start Date:

2022-01-26 00:00:00

Course Overview

❗The content presented here is sourced directly from Youtube platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [October 07th, 2023]

Learn about Computer Vision and Perception for Self Driving Cars. This series focuses on the different tasks that a Self Driving Car Perception unit would be required to do. Course by Robotics with Sakshay. / @roboticswithsakshay Course Contents and Links ⌨ (0:00:00) Introduction ⌨ (0:02:16) Fully Convolutional Network | Road Segmentation ???? Kaggle Dataset: ???? Kaggle Notebook: ???? KITTI Dataset: ???? Fully Convolutional Network Paper: ???? Hand Crafted Road Segmentation: Udacity Self Driving Cars Advanced La... ???? Deep Learning and CNNs: But what is a neural network? | Chapt... ⌨ (0:20:45) YOLO | 2D Object Detection ???? Kaggle Competition/Dataset: ???? Visualization Notebook: ???? YOLO Notebook: ???? Playlist on Fundamentals of Object Detection: CNN-Object Detection ???? Blog on YOLO: ???? YOLO Paper: ⌨ (0:35:51) Deep SORT | Object Tracking ???? Dataset: ???? Notebook/Code: ???? Blog on Deep SORT: / object-tracking-using-deepsort-in-tensorfl... ???? Deep SORT Paper: ???? Kalman Filter: Understanding Kalman Filters ???? Hungarian Algorithm: ???? Cosine Distance Metric: ???? Mahalanobis Distance: ???? YOLO Algorithm: YOLO | 2D Object Detection | Percepti... ⌨ (0:52:37) KITTI 3D Data Visualization | Homogenous Transformations ???? Dataset: ???? Notebook/Code: ???? LIDAR: ???? Tesla doesn't use LIDAR: ⌨ (1:06:45) Multi Task Attention Network (MTAN) | Multi Task Learning ???? Dataset: ???? Notebook/Code: ???? Data Visualization: ???? MTAN Paper: ???? Blog on Multi Task Learning: ???? Image Segmentation and FCN: Fully Convolutional Network | Road Se... ⌨ (1:20:58) SFA 3D | 3D Object Detection ???? Dataset: ???? Notebook/Code: ???? Data Visualization: ???? Data Visualization Video: KITTI 3D Data Visualization | Homogen... ???? SFA3D GitHub Repository: ???? Feature Pyramid Networks: / understanding-feature-pyramid-networks-for... ???? Keypoint Feature Pyramid Network: ???? Heat Maps: ???? Focal Loss: / understanding-focal-loss-a-quick-read ???? L1 Loss: ???? Balanced L1 Loss: ???? Learning Rate Decay: / learning-rate-decay-and-methods-in-deep-le... ???? Cosine Annealing: ⌨ (1:40:24) UNetXST | Camera to Bird's Eye View ???? Dataset: ???? Dataset Visualization: ???? Notebook/Code: ???? UNetXST Paper: ???? UNetXST Github Repository: ???? UNet: ???? Image Transformations: ???? Spatial Transformer Networks: