In this blog post, we are going to learn about the Vision Transformer (ViT). It is a pure Transformer based architecture used for image classification […]
Category: Computer Vision
Nikhil Tomar
MODNet: Real-Time Trimap-Free Portrait Matting via Objective Decomposition
In this work, we present a lightweight matting objective decomposition network (MODNet) for portrait matting in real-time with a single input image. MODNet inputs a […]
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 […]
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) […]
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+, […]
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 […]
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 […]
Squeeze and Excitation Networks
Convolutional Neural Network (CNN) has been most widely used in the field of computer vision and visual perception to solve multiple tasks such as image […]
What is Residual Network or ResNet?
Deep neural networks have become popular due to their high performance in real-world applications, such as image classification, speech recognition, machine translation and many more. […]
What is Transfer Learning? – A Simple Introduction.
Transfer Learning is a technique in machine learning where we reuse a pre-trained model to solve a different but related problem. It is one of […]