TinyDecisionTreeClassifier: Embedded C++ library for training and applying decision trees on the edge

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21460%2F24%3A00378675" target="_blank" >RIV/68407700:21460/24:00378675 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1016/j.softx.2024.101778" target="_blank" >https://doi.org/10.1016/j.softx.2024.101778</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.softx.2024.101778" target="_blank" >10.1016/j.softx.2024.101778</a>

Jazyk výsledku

angličtina

Název v původním jazyce

TinyDecisionTreeClassifier: Embedded C++ library for training and applying decision trees on the edge

Popis výsledku v původním jazyce

Machine learning and AI remain hot topics in research. However, most machine-learning models are trained and applied to big data. Major electronics parts manufacturers are actively working on simplifying the deployment of machine learning models to their chips. Software companies provide microcontroller code generation after the training data are uploaded to their platform. Unfortunately, most of the available open-source solutions do not support training models on the edge. The proposed TinyDecisionTreeClassifier is a standalone open-source C++ library that allows both training and deployment on the edge. This paper also covers the deployment and benchmark of the software performance and power consumption on some of the commonly used microcontrollers.

Název v anglickém jazyce

TinyDecisionTreeClassifier: Embedded C++ library for training and applying decision trees on the edge

Popis výsledku anglicky

Machine learning and AI remain hot topics in research. However, most machine-learning models are trained and applied to big data. Major electronics parts manufacturers are actively working on simplifying the deployment of machine learning models to their chips. Software companies provide microcontroller code generation after the training data are uploaded to their platform. Unfortunately, most of the available open-source solutions do not support training models on the edge. The proposed TinyDecisionTreeClassifier is a standalone open-source C++ library that allows both training and deployment on the edge. This paper also covers the deployment and benchmark of the software performance and power consumption on some of the commonly used microcontrollers.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/TM04000062" target="_blank" >TM04000062: Vývoj platformy pro udržování a monitorování fyzické kondice v izolovaných, uzavřených a extrémních prostředích</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

SoftwareX

ISSN

2352-7110

e-ISSN

2352-7110

Svazek periodika

27

Číslo periodika v rámci svazku

September

Stát vydavatele periodika

AT - Rakouská republika

Počet stran výsledku

7

Strana od-do

—

Kód UT WoS článku

001252828400001

EID výsledku v databázi Scopus

2-s2.0-85195442432