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1.
Development of the web service for grocery store receipt recognition and subsequent analysis of the nutritional value of the products purchased
Pavel Nesterov, 2023, master's thesis

Abstract: The objective of this study is to tackle the worldwide problem of cardiovascular diseases (CVDs). These diseases represent the foremost reason for mortality on a global scale, accounting for approximately 17.9 million deaths annually. Unhealthy eating habits are one of the most frequent causes for CVD in the world and are addressed in various ways, including digital technologies. The goal of this project i`s to develop a web service that enables a non-intrusive way of tracking food consumption and monitoring the dynamics of nutrient intake compared to the traditional "record-every-meal" type of tracking. We followed a design science research approach to develop the web service. The web service employs semantic similarity algorithms and enables human feedback to improve its performance. It will be developed using the Serverless framework and deployed on the AWS platform. Receipt recognition will be performed using AWS Textract, and the nutritional value of the products will be obtained from publicly available databases. This approach aims to create an innovative and user-friendly method for tracking food consumption and nutrient dynamics.
Keywords: Healthy eating, Grocery store receipt, Nutritional analysis, Daily intake monitoring, machine learning, chatbot
Published in DKUM: 14.09.2023; Views: 404; Downloads: 18
.pdf Full text (1,28 MB)

2.
Umetna inteligenca – trenutni in prihodnji izzivi bančništva
Jasmina Gergorec, 2020, undergraduate thesis

Abstract: Uporaba orodij za umetno inteligenco se je v zadnjem času stopnjevala v vseh gospodarskih panogah, med drugim tudi zaradi naraščajočega obsega digitalnih podatkov in vse večje računalniške zmogljivosti. Umetna inteligenca spreminja vse vidike poslovanja, tudi v bančništvu. Banke si danes ne morejo več privoščiti dolge čakalne vrste in pogoste obiske njihovih poslovalnic. Potrebujejo preobrazbo, da bi lahko sledile pričakovanjem svojih strank. Poglobljeno in strojno učenje so izboljšale izkušnje s strankami. Umetna inteligenca vključuje obdelavo naravnega jezika, prepoznavanje govora in strojni vid. Na izbiro imamo več vrst tehnik, ene izmed teh so: nevronske mreže, genetski algoritem ali mehka logika. Motivi za uvajanje umetne inteligence v bančništvo so predvsem odpravljanje človeških napak, boljši regulativni nadzor, hitrejše prepoznavanje in obvladovanje tveganj, prepoznavanje goljufij, boljša finančna varnost, kar se odraža pri nižjih stroških poslovanja ter predstavlja konkurenčno prednost posamezne banke.
Keywords: Umetna inteligenca, bančništvo, chatbot, strojno učenje, obdelava naravnega jezika
Published in DKUM: 30.11.2020; Views: 1390; Downloads: 194
.pdf Full text (620,32 KB)

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