TensorFlow

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Human Face Detection using Multi-task Cascaded Convolutional Networks in TensorFlow

In recent years, advances in machine learning and deep learning techniques have revolutionized the field of computer vision. With the help of these techniques, we can now detect and identify objects in real time with remarkable accuracy. One of the most popular tasks in computer vision is human face detection,...

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Implementing Linear Regression in TensorFlow

TensorFlow is a powerful library for machine learning that allows for the easy implementation of various algorithms, including linear regression. In this tutorial, we will be using TensorFlow tape gradient to implement a linear regression model and plot the loss graph and x and y on matplotlib. First, we will...

VGG19 UNET 0

VGG19 UNET Implementation in TensorFlow

In this tutorial, we are going to implement the U-Net architecture in TensorFlow, where we will replace its encoder with a pre-trained VGG19 architecture. The VGG19 is already trained on the ImageNet classification dataset. Therefore, it would have already learned the required features, which would help to boost the overall...

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Deep Learning based Background Removal from Images using TensorFlow and Python

In this tutorial, we are going to learn how to use deep learning to remove background from images with TensorFlow. In short, we’ll use DeepLabV3+, a semantic segmentation based model to extract the background and foreground mask from the image. We are going to use these masks to extract the...

Implementing Custom layer in TensorFlow 0

Custom Layer in TensorFlow using Keras API

The majority of the people interested in deep learning must have used the TensorFlow library. It is the most popular and widely used deep learning framework. We have used the different layers provided by the tf.keras API to build different types of deep neural networks. But, there are many times...

VGG16 UNET implementation in TensorFlow 0

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 VGG16 implementation from the TensorFlow library. The UNET encoder would learn the features from scratch, while the VGG16 is already trained on the...

Squeeze & Excitation Network 1

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 to implement the Squeeze and Excitation module in TensorFlow and PyTorch. What is Squeeze and Excitation Network? The squeeze and excitation attention mechanism...