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Weighted atlas auto-context with application to multiple organ segmentation.

, , , and . WACV, page 1-9. IEEE Computer Society, (2016)

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DIIP-Dataset for Pig interaction identification with an Enriched Environment., and . (March 2023)Multi-part segmentation for porcine offal inspection with auto-context and adaptive atlases., , , and . Pattern Recognit. Lett., (2018)Automated Classification for Visual-Only Postmortem Inspection of Porcine Pathology., , and . IEEE Trans Autom. Sci. Eng., 17 (2): 1005-1016 (2020)Segmentation of organs in pig offal using auto-context., , , and . ISBI, page 1324-1328. IEEE, (2016)A Combined Deep Learning GRU-Autoencoder for the Early Detection of Respiratory Disease in Pigs Using Multiple Environmental Sensors., , , and . Sensors, 18 (8): 2521 (2018)Video Analysis Using Deep Learning for Automated Quantification of Ear Biting in Pigs., , , and . IEEE Access, (2023)Porcine lie detectors: Automatic quantification of posture state and transitions in sows using inertial sensors., , , , and . Comput. Electron. Agric., (2016)Dancing with horses: automated quality feedback for dressage riders., , , , and . UbiComp, page 325-336. ACM, (2015)Freedom to lie: How farrowing environment affects sow lying behaviour assessment using inertial sensors., , , and . Comput. Electron. Agric., (2019)Ear biting in pigs - a welfare challenge., , , and . (December 2022)