A pseudo-softmax function for hardware-based high speed image classification
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DOI: 10.1038/s41598-021-94691-7
Abstract: In this work a novel architecture, named pseudo-softmax, to compute an approximated form of the softmax function is presented. This architecture can be fruitfully used in the last layer of Neural Networks and Convolutional Neural… read more here.
Keywords: softmax function; neural networks; pseudo softmax; hardware ... See more keywords
An Empirical Evaluation of Enhanced Performance Softmax Function in Deep Learning
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DOI: 10.1109/access.2023.3265327
Abstract: This article present a highly efficient and performance-enhanced Softmax Function (SF) designed for a deep neural network accelerator. The SF is an essential component of deep learning models, primarily used in the classification layer, and… read more here.
Keywords: performance; accuracy; design; deep learning ... See more keywords
Base-2 Softmax Function: Suitability for Training and Efficient Hardware Implementation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems I: Regular Papers"
DOI: 10.1109/tcsi.2022.3175534
Abstract: The softmax function is widely used in deep neural networks (DNNs), its hardware performance plays an important role in the training and inference of DNN accelerators. However, due to the complexity of the traditional softmax,… read more here.
Keywords: base softmax; inline formula; function; softmax function ... See more keywords
Efficient Precision-Adjustable Architecture for Softmax Function in Deep Learning
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DOI: 10.1109/tcsii.2020.3002564
Abstract: The softmax function has been widely used in deep neural networks (DNNs), and studies on efficient hardware accelerators for DNN have also attracted tremendous attention. However, it is very challenging to design efficient hardware architectures… read more here.
Keywords: softmax function; deep learning; function; precision adjustable ... See more keywords
Aggressive Approximation of the SoftMax Function for Power-Efficient Hardware Implementations
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems II: Express Briefs"
DOI: 10.1109/tcsii.2021.3120495
Abstract: Neural Network models most often exploit the SoftMax function in the classification stage for computing probabilities through exponentiation and division operations. To reduce the complexity and the energy consumption of such stage, several hardware-friendly approximation… read more here.
Keywords: hardware; approximation; aggressive approximation; approximation softmax ... See more keywords
Residual and Past Discrete Tsallis and Renyi Extropy with an Application to Softmax Function
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DOI: 10.3390/e24121732
Abstract: In this paper, based on the discrete lifetime distribution, the residual and past of the Tsallis and Renyi extropy are introduced as new measures of information. Moreover, some of their properties and their relation to… read more here.
Keywords: function; renyi extropy; tsallis renyi; residual past ... See more keywords