Digital Hardware Implementations of Spiking Neural Networks With Selective Input Sparsity for Edge Inferences in Controlled Image Acquisition Environments
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Circuits and Systems II: Express Briefs"
DOI: 10.1109/tcsii.2023.3260704
Abstract: Digital hardware implementations of Spiking Neural Networks designed using Selective Input Sparsity (SIS) are proposed for edge inference applications in image classification where the image acquisition environment is controlled. These sparsely connected networks are well-suited… read more here.
Keywords: neural networks; spiking neural; digital hardware; hardware implementations ... See more keywords
Hardware implementations of computer-generated holography: a review
Sign Up to like & getrecommendations! Published in 2020 at "Optical Engineering"
DOI: 10.1117/1.oe.59.10.102413
Abstract: Abstract. Computer-generated holography (CGH) is a technique to generate holographic interference patterns. One of the major issues related to computer hologram generation is the massive computational power required. Hardware accelerators are used to accelerate this… read more here.
Keywords: generated holography; hardware implementations; hardware; computer generated ... See more keywords