Researchers Propose a Novel Framework ‘LilNetX’ For Training Deep Neural Network With Extreme Model Compression, and Structured Sparsification & How It Improves The Computer Vision Tasks

In this research, the researchers from the paper ‘ LilNetX: Lightweight Networks with EXtreme Model Compression and Structured Sparsification’ talk about the importance of larger parameter-heavy and computationally costly architectures in deep neural networks (DNNs) and how it improves the computer vision tasks. They also mentioned in the paper that it is not as simple as it seems since, as the DNNs become more common in the business, they are frequently required to be trained multiple times, communicated across the …

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