A tiny CNN for embedded electronic skin systems
The quest for efficient Tiny Machine Learning on Microcontroller Units is increasing rapidly
due to the vast application spectrum made possible with the advancement of Tiny ML. One …
due to the vast application spectrum made possible with the advancement of Tiny ML. One …
Language Application in Social Networking Activities Based on Embedded Computing
Y Yang, R Ma - 2023 International Conference on Computer …, 2023 - ieeexplore.ieee.org
This paper investigates the application analysis of language in social network activities
based on embedded computing. First, this paper points out the challenges posed by the …
based on embedded computing. First, this paper points out the challenges posed by the …
A Fully Probabilistic Model for Sigmoid Approximation and Its Hardware-Efficient Implementation
W Lu, M Lu, X Zhang, Z Lu, M Sun… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The sigmoid function is a representative activation function in shallow neural networks. Its
hardware realization is challenging due to the complex exponential and reciprocal …
hardware realization is challenging due to the complex exponential and reciprocal …
Tiny Machine Learning Environment: Enabling Intelligence on Constrained Devices
F Sakr - 2023 - qmro.qmul.ac.uk
Running machine learning algorithms (ML) on constrained devices at the extreme edge of
the network is problematic due to the computational overhead of ML algorithms, available …
the network is problematic due to the computational overhead of ML algorithms, available …
A Novel Fully Hardware-Implemented SVD Solver Based on Ultra-Parallel BCV Jacobi Algorithm
T Hu, X Li, X Yu, S Ren, L Yan, X Bai… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Efficient FPGA-based floating-point singular value decomposition (SVD) is challenging for its
enormous complexity with the rapid growth of the matrix dimension. Numerous hardware …
enormous complexity with the rapid growth of the matrix dimension. Numerous hardware …