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…

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UNET 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…

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Extract and Saving Frame from Videos in Python

In this post, we are going to learn and build a python program where we are going to extract and save frames from videos using the OpenCV…

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What 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…

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What 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…

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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 like GPU’s…

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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 2.2 and…

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UNET Segmentation with Pretrained MobileNetV2 as Encoder

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 use pre-trained…

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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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Introduction to autoencoder

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 who are…

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