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...

A human like robot 0

Why Deep Learning is not Artificial General Intelligence (AGI)

With the development in the field of deep learning, it has become a frontier in solving multiple challenging problems in computer vision, games, self-driving cars and many more.  Deep learning has even achieved superhuman performance in some tasks, but still, it lacks some fundamental features which are required for a...

PP-LiteSeg Architecture 0

PP-LiteSeg: A Superior Real-Time Semantic Segmentation Model

PP-LiteSeg is a lightweight encoder-decoder architecture designed for real-time semantic segmentation. It consists of three modules: Encoder: Lightweight network Aggregation: Simple Pyramid Pooling Module (SPPM) Decoder: Flexible and Lightweight Decoder (FLD) and Unified Attention Fusion Module (UAFM) Encoder The STDCNet is the encoder for the proposed PP-LiteSeg for its high...

0

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...

0

UDP Client-Server Implementation in C

There are two major communication protocols: TCP and UDP. These protocols are used to transport data between the client and the server. In one of my previous posts, we have implemented: TCP Client-Server Implementation in C In this tutorial, we are going to build a simple UDP client-server program in...

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...

Semi-supervised learning 0

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 to train the model. It is a hybrid approach between supervised learning and unsupervised learning. The basic difference between the two is that...

File Transfer using TCP Socket in Python3 0

File Transfer using TCP Socket in Python3

In today’s tutorial, we are going to learn to do file transfer using a TCP socket in the python3 programming language. This is the most basic file transfer program that we can do using a client-server architecture. Here, we are going to do the build a client and a server...