RESUNET refers to Deep Residual UNET. It’s an encoder-decoder architecture developed by Zhengxin Zhang et al. for semantic segmentation. It was initially used for the […]
Category: Computer Vision
Nikhil TomarWhat is UNET?
UNET is an architecture developed by Olaf Ronneberger and his team at the University of Freiburg in 2015 for biomedical image segmentation. It is a […]
Data Augmentation for Semantic Segmentation – Deep Learning
All the technological advancements in the field of Artificial Intelligence (AI) is facilitated due to the availability large amount of dataset and the computational hardware’s […]
DCGAN – Implementing Deep Convolutional Generative Adversarial Network in TensorFlow
In this tutorial, we are going to implement a Deep Convolutional Generative Adversarial Network (DCGAN) on Anime faces dataset. The code is written in TensorFlow […]
UNET Segmentation with Pretrained MobileNetV2 as Encoder
In this tutorial, we are going to work on UNet segmentation and use it for biomedical image segmentation tasks. This time we are going to […]
Building Convolutional Autoencoder using TensorFlow 2.0
We are going to continue our journey on the autoencoders. In this article, we are going to build a convolutional autoencoder using the convolutional neural […]
Introduction to Autoencoders
In today’s article, we are going to discuss a neural network architecture called autoencoders. This article is aimed at Machine Learning and Deep Learning beginners […]
Polyp Segmentation using UNET in TensorFlow 2.0
In this tutorial, we will learn about how to perform polyp segmentation using deep learning, UNet architecture, OpenCV, and other libraries. We will use a […]
Review: One Model To Learn Them All
Recent advancement in the field of deep learning has enabled us to develop models that yield impressive results across various fields, from image classification, object […]
What is Data Augmentation?
Data augmentation is a process that enables you to increase the amount of training data by making reasonable modifications in your existing data. It helps […]