Deep Neural Network Capsules A recent paper on Capsules has many important insights for revolutionizing learning in Deep Neural Networks. Let us see why! Interesting characteristics of capsule...

Neural Networks Building Blocks Neural networks are made of smaller modules or building blocks, similarly to atoms in matter and logic gates in digital circuits. Once you know what the blocks are...

layout: post title: ‘Segmenting, localizing and counting object instances in an image’ — Segmenting, localizing and counting object instances in an image When we visually perceive the world, w...

Adversarial predictive networks By Lukasz Burzawa, Abhishek Chaurasia and Eugenio Culurciello We wanted to test the idea that predictive neural network like CortexNetwould benefit from simultane...

Memory, attention, sequences We have seen the rise and success of categorization neural networks. The next big step in neural network is to make sense of complex spatio-temporal data coming from...

layout: post title: ‘Can We Copy the Brain?’ — Can We Copy the Brain? A review of IEEE Spectrum Special Report: Can We Copy the Brain? The IEEE Spectrum this month has a story on syntheti...

LinkNet: neural networks for autonomous driving From our lab: https://codeac29.github.io/projects/linknet/index.html

e-Lab produtions 1997–2013 See our work in image sensors artificial eyes artificial brains biomedical instrumentation neuroscience instruments https://www.slideshare.net/EugenioCulur...

Neuromorphic and Deep Neural Networks Disclaimer: I have been working on analog and mixed-signal neuromorphic micro-chips during my PhD, and in the last 10 years have switched to Deep Learning and...

A new kind of deep neural networks by Alfredo Canziani, Abishek Chaurasia and Eugenio Culurciello There is a new wave of deep neural networks coming. They are the evolution of feed-forward mode...