Comparison of Performance of Optimized HSI CNN models on Desktop and Embedded Platforms
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F21%3A00008992" target="_blank" >RIV/46747885:24220/21:00008992 - isvavai.cz</a>
Alternative codes found
RIV/46747885:24220/21:00009863
Result on the web
<a href="https://ieeexplore.ieee.org/document/9542900" target="_blank" >https://ieeexplore.ieee.org/document/9542900</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.23919/AE51540.2021.9542900" target="_blank" >10.23919/AE51540.2021.9542900</a>
Alternative languages
Result language
angličtina
Original language name
Comparison of Performance of Optimized HSI CNN models on Desktop and Embedded Platforms
Original language description
We compare different platforms for inference of convolutional neural networks in this paper. We trained various neural networks to determine the material in the source hyperspectral cube. Then we convert them to inference format and compare the inference results. We used tools under Xilinx Vitis AI for FPGA implementation. We try to minimize the size of the proposed networks by pruning them and provide further comparisons. FPGA platforms show to be energy efficient but still slower than a graphics card in terms of performance.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
International Conference on Applied Electronics
ISBN
978-802610972-3
ISSN
1803-7232
e-ISSN
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Number of pages
4
Pages from-to
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Publisher name
IEEE
Place of publication
Pilsen, Czech Republic
Event location
Pilsen
Event date
Jan 1, 2021
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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