Advanced Computer Vision Tutorial : Understanding VGG16 with Gradcam

Hi,

Would you like to learn how to use the pre-trained model with Gradcam visualization to identify the most important areas in an image ? 

In this tutorial, we dive deep into the world of advanced computer vision, exploring deep learning techniques to improve the accuracy of your image recognition systems. 

Using the VGG16 model and the Gradcam library, we show you how to identify the specific areas of an image that contribute most to the recognition of your desired object or class.

If you are interested in learning modern Computer Vision course with deep dive with TensorFlow , Keras and Pytorch , you can find it here  : 

Modern Computer Vision™ PyTorch, Tensorflow2 Keras & OpenCV4

Using Python Learn OpenCV4, CNNs, Detectron2, YOLOv5, GANs, Tracking, Segmentation, Face Recognition & Siamese Networks

http://bit.ly/3HeDy1V

Perfect course for every computer vision enthusiastic

Before we continue , I actually recommend this book for deep learning based on Tensorflow and Keras : https://amzn.to/3STWZ2N

Check out our tutorial here : 

Advanced Computer Vision Tutorial : Understanding VGG16 with Gradcam

In this advanced computer vision tutorial, we explore how to use the popular VGG16 model for image recognition, and how to maximize its performance using the...

https://youtu.be/DKvJcK4o3Vw

I also shared the Python instructions to my Github repo in the video description.

Enjoy

Eran

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