In this tutorial, we will use deep learning to build a more robust smile detector than the one we built in the previous tutorial where we used a Haar cascade smile detector. We will use the SMILES dataset to train our convolutional neural network...

In this tutorial, we are going to implement a smile detector algorithm using OpenCV and a pre-trained Haar cascade. Smile detention is a subset of facial recognition technology and can be used for different purposes such as for ensuring that people ...

There are two major problems when training neural networks: overfitting and underfitting. Overfitting is a problem that can occur when the model is too sensitive to the training data. The model will then fail to generalize and perform well on new data...

Training a deep neural network can take hours or even days to complete. It is not practical to train such a neural network every time you want to make predictions. In this case, you can save and then later reload your model.

There are so many books out there that it can be hard to find the right book for you. Below I'll give you my selections for the best 10 Python books for beginners and advanced programmers.

In this tutorial, we are going to see how to detect edges and contours on an image. Edge detection is a fundamental task in computer vision. It can be defined as the task of finding boundaries between regions that have different properties.

Machine learning is the process of building a computer program that automatically learns and adapts to make predictions, recognize patterns, and make decisions. It’s what makes Siri seem so intelligent and it has a wide range of applications ...

In this tutorial, we will see how to rotate images with OpenCV using some built-in functions. The first one is cv2.getRotationMatrix2D which, as its name suggests, will give us the transformation matrix that we will use to rotate the image ...