Hello Viewers, in this video, It is explained that how one can implement a deep RCNN for detecting 'STOP' traffic signs from image and videos in both offline and real time mode.
Also, it is shown that how one can use MATLAB's Labeler app to create database for training.
Here, transfer learning is used and for fine tuning, a pre trained RCNN is re trained on our own image dataset which is created with help of Image Labeler app.
This video has following contents:
- Introduction.
- What is Deep R-CNN?
- Proposed Scheme using Deep R-CNN.
- Understanding MATLAB’s Image Labeler for image database creation.
- MATLAB Code for training.
- MATLAB Code for testing.
- Code execution and result analysis.
Links of previous videos:
1. How to create a Deep CNN: Click Here
2. ECG signals classification using wavelet features and deep CNN: Click Here
3. Implementing deep CNN in Python using TF and Keras (Face Mask detection): Click Here
Download Resources:
1. Test Video: Download (Source: Mathworks.com)
2. Traffic Sign Image Database: Download
Sir I've watched the video completely and it really helped a lot. My question is in case you are implementing a similar thing that is not pretrained how would you go about it? Meaning you want to start from the scratch
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