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- W3000089636 abstract "The recognition of individual organs by machine vision is an important step towards the processing of lamb meat and the extraction of edible offal. This paper presents the first semantic segmentation method to localise and label sheep organs in images of the extracted organ package. The challenges around the semantic segmentation of lamb organs include the lack of available data sets, the variable orientation, shape and appearance of organs, and the wet and specular surface. To address these challenges, we created a new dataset for sheep organ segmentation consisting of images and pixel-wise labels for seven types of organs and tissues. To produce baseline results on the data set, a convolutional neural network is trained to partition images into segments corresponding to individual organs." @default.
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- W3000089636 date "2019-12-01" @default.
- W3000089636 modified "2023-09-23" @default.
- W3000089636 title "Semantic Segmentation of Sheep Organs by Convolutional Neural Networks" @default.
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- W3000089636 doi "https://doi.org/10.1109/ivcnz48456.2019.8961025" @default.
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