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Title: Using Convolutional Neural Networks for Detecting Acrylamide in Biscuit Manufacturing Process
Authors: Topçuoğlu, Dilruba
Mentes, Berat Utkan
Aşkın, Nur
Şengül, Ayşe Damla
Cankut, Zeynep Deniz
Akdemir, Talip
Ceylan, Murat
Keywords: Acrylamide
Deep Learning
Image Processing
CNN Algorithm
Issue Date: 2022
Publisher: Scitepress
Abstract: Based on a research in 2002 (Ozkaynak & Ova, 2006), acrylamide substance is formed when excessive heat treatment (e.g. frying, grilling, baking) is applied to starch-containing products. This substance contains carcinogenic and neurotoxicological risks for human health. The acrylamide levels are controlled by random laboratory sampling. This control processes which are executed by humans, cause a prolonged and error prone process. In this study, we offer a Convolutional Neural Network (CNN) model, which provides acceptable precision and recall rates for detecting acrylamide in biscuit manufacturing process.
Description: 11th International Conference on Data Science, Technology and Applications (DATA) -- JUL 11-13, 2022 -- Lisbon, PORTUGAL
ISBN: 978-989-758-583-8
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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