First, we apply Approximate Computing Techniques (ACTs) to reduce the computational complexity of ML algorithms. Then, we design custom Hardware Accelerators to ...
Embedded Machine Learning: Emphasis on Hardware Accelerators and Approximate Computing for Tactile Data Processing. H Younes. Università degli studi di Genova ...
In this paper, we demonstrate the feasibility and efficiency of approximate computing techniques (ACTs) in the embedded Support Vector Machine (SVM) ...
Due to the errorresilient nature of image and video processing applications, approximating certain aspects can significantly improve computing time and ...
The paper presents our recent achievements in the implementation of embedded machine learning methods for near sensors tactile data processing.
Apr 25, 2024 · Embedded Machine Learning: Emphasis on Hardware Accelerators and Approximate Computing for Tactile Data Processing. University of Genoa ...
Approximate Computing Methods for Embedded Machine Learning
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An assessment of approximate computing methods at algorithmic, architecture, and circuit levels and draws perspectives for further developments and ...
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What are machine learning accelerators?
Machine learning has lately been used to create solutions for complex tasks such as picture and speech recognition, as well as tactile data processing, with ...
Jun 28, 2021 · propose hardware accelerators in section 6.3, and introduce experimental results based on such hardware in section 6.3.3. 6.3 Hardware ...
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In this regard, this paper presents our recent achievements in the implementation of embedded machine learning methods for near sensors tactile data processing.