Convolution Neural Network (CNN) – Fundamental of Deep Learning
Convolutional Neural Network (CNN) is used to solve a wide range of visual tasks such as image classification, object detection, semantic segmentation, and many more. CNN consists…
Read moreUNET Implementation in TensorFlow using Keras API
In this post, you will learn how to implement UNET architecture in TensorFlow using Keras API. The post helps you to learn about UNET, and how to…
Read moreWhy do we need GPU for Deep Learning?
The current era started to move towards Artificial Intelligence, which massively impacted the world with its ability to achieve the tasks that were a dream of humanity….
Read moreWhat is RESUNET
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 road extraction…
Read moreWhat is UNET?
UNET is an architecture developed by Olaf Ronneberger et al. for Biomedical Image Segmentation in 2015 at the University of Freiburg, Germany. It is one of the…
Read moreData 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 like GPU’s…
Read moreDCGAN – 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 2.2 and…
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GAN – What is Generative Adversarial Network?
Generative Adversarial Network or GAN is a machine learning approach used for generative modelling designed by Ian Goodfellow and his colleagues in 2014. It is made of…
Read moreOpenAI GPT-3: The successor of OpenAI GPT-2
The research lab OpenAI has released a preprint arXiv paper, titled “Language Models are Few-Shot Learners” or OpenAI GPT-3, which is a continuation of their previous work…
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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 network (CNN)…
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