[ FreeCourseWeb ] Udemy - Mask R-CNN - Practical Deep Learning Segmentation in 1 hour

[ FreeCourseWeb.com ] Mask R-CNN - Practical Deep Learning Segmentation in 1 hour

Download More Courses Visit and Support Us -->> https://FreeCourseWeb.com



MP4 | h264, 1280x720 | Lang: English | Audio: aac, 48000 Hz | 2h 10m | 2.84 GB
What you'll learn
What is Instance Segmentation
How to take object segmentation further using Mask RCNN
Secret tip to multiply your data using Data Augmentation.
How to use AI to label your dataset for you.
Find out how to train your own custom Mask R-CNN from scratch.
Pothole Detection using Mask R-CNN
Step-by-step instructions on how to Execute, Annotate, Train and Deploy Custom Mask R-CNN models.

Requirements
Background in OpenCV & Computer Vision
Have prior experience in Python using Anaconda.
A PC/Laptop with CUDA-enabled Nvidia graphics Card for training - We use Ubuntu for training.
Create a Free Account with Supervisely.
Description
***Important Notes***

This is a practical-focused course. While we do provide an overview of Mask R-CNN theory, we focus mostly on helping you get Mask R-CNN working step-by-step.

Learn how we implemented Mask R-CNN Deep Learning Object Detection Models From Training to Inference - Step-by-Step

Use Winrar to Extract. And use a shorter path when extracting, such as C: drive

ALSO ANOTHER TIP: You Can Easily Navigate Using Winrar and Rename the Too Long File/ Folder Name if Needed While You Cannot in Default Windows Explorer. You are Welcome ! :)

Download More Courses Visit and Support Us -->> https://FreeCourseWeb.com

Get More Tutorials and Support Us -->> https://DevCourseWeb.com

We upload these learning materials for the people from all over the world, who have the talent and motivation to sharpen their skills/ knowledge but do not have the financial support to afford the materials. If you like this content and if you are truly in a position that you can actually buy the materials, then Please, we repeat, Please, Support Authors. They Deserve it! Because always remember, without "Them", you and we won't be here having this conversation. Think about it! Peace...