Search Results for: "neural network"

LSTM Vs GRU in Recurrent Neural Network: A Comparative Study

Long Short Term Memory in short LSTM is a special kind of RNN capable of learning long term sequences. They were introduced by Schmidhuber and Hochreiter in 1997. It is explicitly designed to avoid long term dependency problems. Remembering the long sequences for a long period of time is its way of working. 


Hands-On Guide To Differential Digital Signal Processing Using Neural Networks

Digital Signal Processors take waveforms in voice, audio, video, temperature, and then mathematically manipulate them. The key idea of a DSP is to create complex, realistic signals by precisely controlling and tuning their many parameters.

How To Confuse a Neural Network Using Fast Gradient Sign Method?

Many machine learning models, including neural networks, consistently misclassify the adversarial examples. Adversarial examples are nothing but specialised inputs created to confuse neural networks, ultimately resulting in misclassification of the result. These notorious inputs are almost the same as the original image to human eyes but cause a neural network to fail to identify the image’s content.

Applying Neural Network Model To The Problem Of Cell Size Control

Cell growth and division are two significant areas of research in the field of cell…

Are Deep Neural Networks Unequivocally Better Than Lidar?

Tesla has always had a unique approach towards self-driving cars. The electric car company has…


Beginner’s Guide To Lucid: A Network For Visualizing Neural Networks

Computer Vision or CV can be defined as a field of study that aims to…

MIT Researchers Develop Single Deep Neural Network For Autonomous Vehicles

Rapidly developing sensor technology and software processing has enabled autonomy for trucks — improving fleet…


Guide To XBNet: An Extremely Boosted Neural Network

A few days back, a naval architecture was launched, ‘XBNet’, which stands for ‘Extremely Boosted Neural Network’, which combines gradient boosted tree with a feed-forward neural network, making the model robust for all performance metrics.

MIT Weaves Neural Networks Into Shirts, Creates First Of Its Kind Digital Fibre

MIT researchers have come out with a digital fabric. The fibre, embedded in a shirt,…

Recurrent Neural Network

Implementing A Recurrent Neural Network (RNN) From Scratch

In this article we implement a character level recurrent neural network (RNN) from scratch in Python using NumPy.

Top 8 Books To Learn Convolutional Neural Networks

Yann Lecun changed computer vision and, for that matter, artificial intelligence forever with CNNs.

Guide To Asymmetric Non-local Neural Networks Using PaddleSeg 

PaddleSeg is an Image segmentation framework based on Baidu’s PaddlePaddle(Parallel Distributed Deep Learning). It provides high performance and efficiency, SOTA segmentation models optimized for MultiNode and MultiGPU production systems.