Shivam Chandhok

Table of Contents Triplet Loss with Keras and TensorFlow Configuring Your Development Environment Having Problems Configuring Your Development Environment? Project Structure Implementing Siamese Model and Triplet Loss Summary Credits Citation Information Triplet Loss with Keras and TensorFlow In today’s tutorial,…

Table of Contents Building a Dataset for Triplet Loss with Keras and TensorFlow Labeled Faces in the Wild Dataset Configuring Your Development Environment Having Problems Configuring Your Development Environment? Project Structure Creating Our Configuration File Creating Our Data Pipeline Preprocessing…

Table of Contents Face Recognition with Siamese Networks, Keras, and TensorFlow Face Recognition Face Recognition: Identification and Verification Identification via Verification Metric Learning: Contrastive Losses Contrastive Losses Summary Credits Citation Information Face Recognition with Siamese Networks, Keras, and TensorFlow In…

Table of Contents CycleGAN: Unpaired Image-to-Image Translation (Part 1) Introduction Unpaired Image Translation CycleGAN Pipeline and Training Loss Formulation Adversarial Loss Cycle Consistency Summary Citation Information CycleGAN: Unpaired Image-to-Image Translation (Part 1) In this tutorial, you will learn about image-to-image…

In this tutorial, you will learn the concept behind Fully Convolutional Networks (FCNs) for segmentation. In addition, we will see how we can use Torch Hub to import a pre-trained FCN model and use it in our projects to get…

In this tutorial, you will learn the architectural details of Progressive GAN, which enable it to generate high-resolution images. In addition, we will see how we can use Torch Hub to import a pre-trained PGAN model and use it in…

In today’s tutorial, we will be looking at image segmentation and building our own segmentation model from scratch, based on the popular U-Net architecture. This lesson is the last of a 3-part series on Advanced PyTorch Techniques: Training a DCGAN…

An essential part of any Deep Learning based system is to structure the data loading pipeline such that it can be seamlessly integrated with your deep learning model. In this tutorial, we will understand the working of data loading functionalities…