Convolutional Neural Networks are considered the State-of-the-Art in computer vision related Machine Learning tasks. Soham Chatterjee highlights the limitations of CNNs and discusses alternate models that closely mirror the way the human brain work. He uses Professor Geoffrey Hinton’s paper, Dynamic Routing Between Capsules, to establish certain points.
Convolutional Neural Networks, popularly called CNNs, have been around for a while; in fact, they are our go-to algorithm for any Computer Vision related task. CNNs are, as of now, the final answer when it comes to computer vision related Machine Learning tasks. They are used widely in object recognition systems, self-driving cars, etc. They can even be used to create new paintings based on the patterns of famous painters of the past! Part of what makes them so widely used is that they are really good at what they do.
Capsule Networks and the Limitations of CNNs Print
Modified on: Mon, 8 Feb, 2021 at 3:00 PM
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