Shypd.aiThe largest open index of AI toolsEmbedded-Neural-Network is a Research & Education tool that collects papers on reducing model sizes and developing ASIC/FPGA accelerators for machine learning. It provides tutorials on hardware accelerators and model compression techniques.
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Embedded-Neural-Network is a comprehensive collection of research papers and tutorials focused on optimizing deep neural networks for embedded applications. The repository curates works aimed at reducing model sizes and developing specialized ASIC/FPGA accelerators for machine learning. It covers various techniques including network compression, parameter sharing, teacher-student mechanisms (distilling), fixed-precision training, sparsity regularizers & pruning, tensor decomposition, and conditional (adaptive) computing. Additionally, it provides resources on hardware accelerator benchmarks and platform analysis, with a specific focus on Recurrent Neural Networks and Convolutional Neural Networks. This collection is an invaluable resource for researchers and engineers working on efficient deployment of AI models.
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