You can master Computer Vision, Deep Learning, and OpenCV - PyImageSearch
Now that we’ve trained our model and serialized it, we need to load it from disk. As a practical application of model serialization, I’ll be demonstrating how to classify individual images from the Animals dataset and then display the classified…
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The LeNet architecture is a seminal work in the deep learning community, first introduced by LeCun et al. in their 1998 paper, Gradient-Based Learning Applied to Document Recognition. As the name of the paper suggests, the authors’ motivation behind implementing…
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In our previous tutorial, we discussed LeNet, a seminal Convolutional Neural Network in the deep learning and computer vision literature. VGGNet, (sometimes referred to as simply VGG), was first introduced by Simonyan and Zisserman in their 2014 paper, Very Deep…
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Now that we have implemented neural networks in pure Python, let’s move on to the preferred implementation method — using a dedicated (highly optimized) neural network library such as Keras. Today, I will discuss how to implement feedforward, multi-layer networks…
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In this tutorial, you will learn how to generate image batches of (1) normal images and (2) adversarial images during the training process. Doing so improves your model’s ability to generalize and defend against adversarial attacks. Last week we learned…
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In this tutorial, you will learn how to defend against adversarial image attacks using Keras and TensorFlow. So far, you have learned how to generate adversarial images using three different methods: Adversarial images and attacks with Keras and TensorFlow Targeted…
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In this tutorial, you will learn how to perform adversarial attacks using the Fast Gradient Sign Method (FGSM). We will implement FGSM using Keras and TensorFlow. A dataset of images and their labels is critical for understanding adversarial attacksusing FGSM.…
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In this tutorial, you will learn about contrastive loss and how it can be used to train more accurate siamese neural networks. We will implement contrastive loss using Keras and TensorFlow. Previously, I authored a three-part series on the fundamentals…
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In this tutorial, you will learn how to compare two images for similarity (and whether or not they belong to the same or different classes) using siamese networks and the Keras/TensorFlow deep learning libraries. This blog post is part three…
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