Image Classification with Single Class dataset using VGG-16 Transfer Learning
Transfer learning generally refers to a process where a model trained on one problem is used in some way on […]
How to resize all images in the folder using CV2 and Python?
In this post, I will explain how to read multiple images from a folder, resize them, save them in a […]
How to implement CapsuleNet on TensorFlow using Google Colab?
So now we all know that Capsule Networks (by Geoffrey Hinton) is shaking up the AI space and literature state […]
Classification of Objects in Photographs using Pre-trained VGG-16 Model
Convolutional neural networks are now capable of outperforming humans on some computer vision tasks, such as classifying images. That is, […]
How to fine-tune VGG-16 net using Keras on Google Colaboratory?
Training deep neural networks on CPUs is difficult. This tutorial will guide you on how to fine-tune VGG-16 net using […]
VGG-19 Convolutional Neural Network
VGG19 is a variant of the VGG model which in short consists of 19 layers (16 convolution layers, 3 Fully […]
VGG-16 | CNN model for Classification and Detection
VGG16 is a convolutional neural network model proposed by K. Simonyan and A. Zisserman from the University of Oxford in the […]
How to used Google Colab for Deep Learning using Python?
Whether you are a student interested in exploring Machine Learning but struggling to conduct simulations on enormous datasets, or an […]
How to compute peak signal-to-noise ratio (PSNR) between images using Python?
The PSNR block computes the peak signal-to-noise ratio, in decibels, between two images. This ratio is used as a quality […]
How to calculate the Structural Similarity Index (SSIM) between two images with Python?
The Structural Similarity Index (SSIM) is a perceptual metric that quantifies the image quality degradation that is caused by processing […]