Pig Treatment Classification on Thermal Image Data using Deep Learning

Savina Jassica Colaco, Jung Hwan Kim, Alwin Poulose, Zutphen Sanne Van, Suresh Neethirajan, Dong Seog Han

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Recently, image classification has gained recognition in several applications like self-driving cars, security surveillance systems, face detection, etc. The conventional methods have been overtaken by deep learning methods which can detect and classify objects in complex scenarios. In this paper, we propose a simple CNN model for pig treatment classification on thermal images. The proposed model is compared with different deep learning models which are widely used for image classification. The models are evaluated with our own thermal dataset collected using a FLIR camera. The experimental results show the thermal images of different pig treatments are better classified with the proposed model. The proposed model can achieve 99.96% accuracy with a few parameters.

Original languageEnglish
Title of host publicationICUFN 2022 - 13th International Conference on Ubiquitous and Future Networks
PublisherIEEE Computer Society
Pages8-11
Number of pages4
ISBN (Electronic)9781665485500
DOIs
StatePublished - 2022
Event13th International Conference on Ubiquitous and Future Networks, ICUFN 2022 - Virtual, Barcelona, Spain
Duration: 5 Jul 20228 Jul 2022

Publication series

NameInternational Conference on Ubiquitous and Future Networks, ICUFN
Volume2022-July
ISSN (Print)2165-8528
ISSN (Electronic)2165-8536

Conference

Conference13th International Conference on Ubiquitous and Future Networks, ICUFN 2022
Country/TerritorySpain
CityVirtual, Barcelona
Period5/07/228/07/22

Keywords

  • Classification
  • convolutional neural network (CNN)
  • thermal images

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