Introduction to Automatic Speech Recognition

The Automatic Speech Recognition (ASR) systems are widely used nowadays. Some of the most notable uses include Siri, Alexa Google Assistant, Cortana, etc. Let’s understand the fundamentals of...

Data augmentation

Generative Adversarial Networks variants: DCGAN, Pix2pix, CycleGAN

First, make sure you read the first part of this post, Generative models and Generative Adversarial Networks. This post is its continuation.

Layer-specific learning rates

Note: This post answers the question I asked on Cross-Validated: What are the benefits of layer-specific learning rates?

Quick intro to Object detection: R-CNN, YOLO, and SSD

Object detection deals with the detection of object instances in an image. There are a number of methods to accomplish it. The following post summarizes few important object...

Attention

Attention is the technique through which the model focuses itself on a certain region of the image or on certain words in a sentence just like the same...

Backpropagation Through Time

In the earlier post The gradient problem in RNN, you came to know that RNNs have exploding and vanishing gradient problems. This post discusses how exactly the gradients...

Autoencoder: Downsampling and Upsampling

Note: Read the post on Autoencoder written by me at OpenGenus as a part of GSSoC.

Weight initialization in neural nets

In deep learning, the goal is to find the optimum weights of the model to get the desired output. In transfer learning, the network is initialized using the...

Image captioning using encoder-decoder

Note: This post discusses the project I’m doing currently. Check it on kHarshit/image-captioner. The working demo is available on https://imagecaptioner.herokuapp.com.