Classify broiler viscera using an iterative approach on noisy labeled training data

Anders Jørgensen*, Jens Fagertun, Thomas B. Moeslund

*Kontaktforfatter

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

2 Citationer (Scopus)

Abstract

Poultry meat is produced and slaughtered at higher and higher rates and the manual food safety inspection is now becoming the bottleneck. An automatic computer vision system could not only increase the slaughter rates but also lead to a more consistent inspection. This paper presents a method for classifying broiler viscera into healthy and unhealthy, in a data set recorded in-line at a poultry processing plant. The results of the on-site manual inspection are used to automatically label the images during the recording. The data set consists of 36,228 images of viscera. The produced labels are noisy, so the labels in the training set are corrected through an iterative approach and ultimately used to train a convolutional neural network. The trained model is tested on a ground truth data set labelled by experts in the field. A classification accuracy of 86% was achieved on a data set with a large in-class variation.

OriginalsprogEngelsk
TitelAdvances in Visual Computing : 13th International Symposium, ISVC 2018, Las Vegas, NV, USA, November 19 – 21, 2018, Proceedings
RedaktørerKai Xu, Stephen Lin, Richard Boyle, Bilal Alsallakh, Matt Turek, Srikumar Ramalingam, George Bebis, Bahram Parvin, Jing Yang, Jonathan Ventura, Darko Koracin, Eduardo Cuervo
Antal sider10
ForlagSpringer
Publikationsdato2018
Sider264-273
ISBN (Trykt)978-3-030-03800-7
ISBN (Elektronisk)978-3-030-03801-4
DOI
StatusUdgivet - 2018
Begivenhed13th International Symposium on Visual Computing, ISVC 2018 - Las Vegas, NV, USA
Varighed: 19 nov. 201821 nov. 2018

Konference

Konference13th International Symposium on Visual Computing, ISVC 2018
Land/OmrådeUSA
ByLas Vegas, NV
Periode19/11/201821/11/2018
NavnLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Vol/bind11241 LNCS
ISSN0302-9743

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