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Title:Vgrajen sistem za procesiranje video tokov na osnovi strojno pospešenih nevronskih mrež : magistrsko delo
Authors:ID Kosi, Primož (Author)
ID Kramberger, Iztok (Mentor) More about this mentor... New window
ID Kos, Marko (Comentor)
Files:.pdf MAG_Kosi_Primoz_2022.pdf (2,65 MB)
MD5: A23406D97C891EBC7B7B57D236D58AA1
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V magistrskem delu je opisan vgrajen sistem za procesiranje video tokov na osnovi strojno pospešenih nevronskih mrež. Video tok se zajema s kamero ali preko HDMI vmesnika. Sistem je grajen za prepoznavanje predmetov v realnem času. Vhodni video tok se procesira s strojnim pospeševalnikom CoreVectorBlox, ki izvaja nevronske mreže. Nadzoruje ga mehka procesna enota RISC-V. Nevronske mreže so vključene v obliki binarnih podatkov. Povezave posameznih podsistemov so izvedene z AMBA AXI, AHB in APB vodili. Izhodni video tok se prikazuje na zaslonu preko HDMI povezave. Opisani so posamezni deli in delovanje celotnega sistema. V nalogi so predstavljene meritve porabe moči in učinkovitosti prepoznave predmetov.
Keywords:Mikrokrmilniki, programirljiva logična vezja, procesiranje video tokov, strojno pospeševanje, nevronske mreže.
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[P. Kosi]
Year of publishing:2022
Number of pages:1 spletni vir (1 datoteka PDF (X, 54 f.))
PID:20.500.12556/DKUM-82572 New window
UDC:004.312.466(043.2)
COBISS.SI-ID:129780483 New window
Publication date in DKUM:30.09.2022
Views:666
Downloads:87
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:25.08.2022

Secondary language

Language:English
Title:Embedded system for video processing based on hardware accelerated neural networks
Abstract:The master's thesis describes an integrated video stream processing system based on hardware accelerated neural networks. The video stream is captured by a camera or via HDMI interface. The system is built for real-time object recognition. The input video stream is processed by a CoreVectorBlox hardware accelerator, that implements neural networks. It is controlled by a RISC-V soft processing unit. The neural networks are included in the form of binary large objects. Connections of the individual subsystems are implemented by AMBA AXI, AHB and APB buses. The output video stream is displayed on the screen via HDMI connection. The individual components and the operation of the complete system are described. Measurements of power consumption and object recognition performance are presented in the thesis.
Keywords:Microcontrolers, Programmable Logic Device, Video strem processing, hardware acceleration, neural networks.


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