First CNN on GPU

The 2011 paper “Flexible, High Performance Convolutional Neural Networks for Image Classification” by Dan C. Cireşan, Ueli Meier, Jonathan Masci, Luca M. Gambardella, and Jürgen Schmidhuber was a pioneering work in the field of deep learning. It was the...

ImageNet challenge

ImageNet, created by Fei-Fei Li and her team in 2009, represents a transformative milestone in the field of computer vision and machine learning. This extensive dataset, containing over 14 million labeled images across 20,000 categories, enabled the research community...

Feature extraction by neural networks

The authors demonstrated that neural networks with multiple hidden layers can effectively learn compact, meaningful representations of high-dimensional data. These learned representations, or embeddings, can capture the essential structure of the input data,...

Le Net

An early instance of a successful gradient-based learning technique is detailed in the paper “Gradient-Based Learning Applied to Document Recognition” by Y. LeCun et al., published in the Proceedings of the IEEE in 1998. This work exemplifies the practical...

Long Short Term Memory Networks

LSTM networks represented a milestone in addressing the vanishing gradient problem that plagued the training of deep neural architectures. This problem occurs when gradients used to train the network diminish exponentially as they are back-propagated through layers,...