Parvin BulucuNalan ǑzkurtCuneyt GuzelsOsman YıldızGuzels, CuneytBulucu, PervinYildiz, OsmanOzkurt, Nalan2025-10-062021978166543405810.1109/ASYU52992.2021.95990632-s2.0-85123194681https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123194681&doi=10.1109%2FASYU52992.2021.9599063&partnerID=40&md5=4bc8d67a5ff0f17ac30aecefd5568380https://gcris.yasar.edu.tr/handle/123456789/9047https://doi.org/10.1109/ASYU52992.2021.9599063This paper presents a convolutional neural network algorithm for the classification of beef samples electronic nose dataset. Proposed algorithm was tested and results were compared to other works that used the same dataset. Overall proposed algorithm showed high performance results without any pre-processing steps. © 2022 Elsevier B.V. All rights reserved.Englishinfo:eu-repo/semantics/closedAccessBeef Dataset, Convolutional Neural Network, E-nose, Electronic Nose, Beef, Classification (of Information), Convolution, Convolutional Neural Networks, Application Specific, Assesment, Beef Dataset, Convolution Neural Network, Convolutional Neural Network, Neural Networks Algorithms, Performance, Pre-processing Step, Electronic NoseBeef, Classification (of information), Convolution, Convolutional neural networks, Application specific, Assesment, Beef dataset, Convolution neural network, Convolutional neural network, Neural networks algorithms, Performance, Pre-processing step, Electronic noseBeef DatasetElectronic NoseE-noseConvolutional Neural NetworkConference Object