Diagnosis of Broiler Livers by Classifying Image Patches

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3 Citationer (Scopus)

Resumé

The manual health inspection are becoming the bottleneck at poultry processing plants. We present a computer vision method for automatic diagnosis of broiler livers. The non-rigid livers, of varying shape and sizes, are classified in patches by a convolutional neural network, outputting maps with probabilities of the three most common diseases. A Random Forest classifier combines the maps to a single diagnosis. The method classifies 77.6% livers correctly in a problem that is far from trivial.
OriginalsprogEngelsk
TitelImage Analysis : 20th Scandinavian Conference, SCIA 2017, Tromsø, Norway, June 12–14, 2017, Proceedings, Part I
ForlagSpringer
Publikationsdato19 maj 2017
Sider374-385
ISBN (Trykt)978-3-319-59125-4
ISBN (Elektronisk)978-3-319-59126-1
DOI
StatusUdgivet - 19 maj 2017
BegivenhedScandinavian Conference on Image Analysis, SCIA - Tromsø, Norge
Varighed: 12 jun. 201714 jun. 2017
Konferencens nummer: 20
http://scia2017.org

Konference

KonferenceScandinavian Conference on Image Analysis, SCIA
Nummer20
LandNorge
ByTromsø
Periode12/06/201714/06/2017
Internetadresse
NavnLecture Notes in Computer Science
Vol/bind10269
ISSN0302-9743

Fingerprint

broiler chickens
liver
meat processing plants
computer vision
neural networks
methodology

Citer dette

Jørgensen, A., Fagertun, J., & Moeslund, T. B. (2017). Diagnosis of Broiler Livers by Classifying Image Patches. I Image Analysis: 20th Scandinavian Conference, SCIA 2017, Tromsø, Norway, June 12–14, 2017, Proceedings, Part I (s. 374-385). Springer. Lecture Notes in Computer Science, Bind. 10269 https://doi.org/10.1007/978-3-319-59126-1_31
Jørgensen, Anders ; Fagertun, Jens ; Moeslund, Thomas B. / Diagnosis of Broiler Livers by Classifying Image Patches. Image Analysis: 20th Scandinavian Conference, SCIA 2017, Tromsø, Norway, June 12–14, 2017, Proceedings, Part I. Springer, 2017. s. 374-385 (Lecture Notes in Computer Science, Bind 10269).
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title = "Diagnosis of Broiler Livers by Classifying Image Patches",
abstract = "The manual health inspection are becoming the bottleneck at poultry processing plants. We present a computer vision method for automatic diagnosis of broiler livers. The non-rigid livers, of varying shape and sizes, are classified in patches by a convolutional neural network, outputting maps with probabilities of the three most common diseases. A Random Forest classifier combines the maps to a single diagnosis. The method classifies 77.6{\%} livers correctly in a problem that is far from trivial.",
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Jørgensen, A, Fagertun, J & Moeslund, TB 2017, Diagnosis of Broiler Livers by Classifying Image Patches. i Image Analysis: 20th Scandinavian Conference, SCIA 2017, Tromsø, Norway, June 12–14, 2017, Proceedings, Part I. Springer, Lecture Notes in Computer Science, bind 10269, s. 374-385, Scandinavian Conference on Image Analysis, SCIA, Tromsø, Norge, 12/06/2017. https://doi.org/10.1007/978-3-319-59126-1_31

Diagnosis of Broiler Livers by Classifying Image Patches. / Jørgensen, Anders; Fagertun, Jens; Moeslund, Thomas B.

Image Analysis: 20th Scandinavian Conference, SCIA 2017, Tromsø, Norway, June 12–14, 2017, Proceedings, Part I. Springer, 2017. s. 374-385 (Lecture Notes in Computer Science, Bind 10269).

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

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Jørgensen A, Fagertun J, Moeslund TB. Diagnosis of Broiler Livers by Classifying Image Patches. I Image Analysis: 20th Scandinavian Conference, SCIA 2017, Tromsø, Norway, June 12–14, 2017, Proceedings, Part I. Springer. 2017. s. 374-385. (Lecture Notes in Computer Science, Bind 10269). https://doi.org/10.1007/978-3-319-59126-1_31