VGG16 UNET implementation in TensorFlow

VGG16 UNET Implementation in TensorFlow

In this article, we are going to implement the most widely used image segmentation architecture called UNET. We are going to replace the UNET encoder with the…

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Squeeze & Excitation Network

Squeeze and Excitation Implementation in TensorFlow and PyTorch

The Squeeze and Excitation network is a channel-wise attention mechanism that is used to improve the overall performance of the network. In today’s article, we are going…

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Semi-supervised learning

Semi-supervised Learning – Fundamentals of Deep Learning

Semi-supervised learning is a type of machine learning where we use a combination of a large amount of unlabelled data and a small amount of labelled data…

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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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A beautiful mountain scene

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 you to…

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