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 Python3.8 . According to Yann LeCun, the director of Facebook AI, GAN is…
Category: TensorFlow
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 MobileNetV2 as the encoder for the UNet architecture. We are going to integrate…
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) in TensorFlow 2.0. Let us first revise, what are autoencoders? Autoencoders are neural…
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 polyp segmentation dataset to understand how semantic segmentation is applied to real-world data. In polyp…
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 detection, to speech recognition. However, developing the architecture for each problem is a challenge in…
In recent years deep learning is a huge success in the world of computer vision, making deep learning the new tool in the digital image analysis. It has made computers understand the visual data much better than ever before. In this article, I’ll go into details about one specific task in computer vision: Semantic Segmentation using the UNET Architecture.
In this article, we will go through the TensorFlow to build a Convolutional Neural Network that will help you to identify the breed of a dog from its image. In the process, we will use Transfer Learning and learn how to design, train and test models with the provided dataset.