Neural Network
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Ever watched an AI-generated video and wondered how it was made? Or perhaps dreamed of creating your own dynamic scenes, only to be overwhelmed by the complexity or the need
In Deep Learning, Batch Normalization (BatchNorm) and Dropout, as Regularizers, are two powerful techniques used to optimize model performance, prevent overfitting, and speed up convergence. While both have their individual
Feature matching using deep learning is a game-changer for computer vision tasks like panorama stitching, video stabilization, and face recognition, providing greater accuracy and reliability. Dive into how this technology
In this article, we show how to implement Vision Transformer using the PyTorch deep learning library.
In this article, we cover the attention mechanism in neural networks in detail and also implement it using PyTorch
In this post, we’ll learn how to implement a Convolutional Neural Network (CNN) from scratch using Keras. Here, we show a CNN architecture similar to the structure of VGG-16 but
Before studying deep neural networks, we will cover the fundamental components of a simple (linear) neural network. We’ll begin with the topic of linear regression. Since linear regression can be
