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We propose a machine learning based approach to real-time detection and classification assistance for images from unknown environments. While systems for detecting and classifying regular structures like faces in still images are well established, the task of e. g. detecting new morphotypes/objects in an environment is much more complex. The morphotypes/objects are not guaranteed to have apriori known...
Here, we turn our attention to barycentric embeddings and examine their utility for semi-supervised image labelling tasks. To this end, we view the pixels in the image as vertices in a graph and their pairwise affinities as weights of the edges between them. Abstracted in this manner, we can pose the semi-supervised labelling problem into a graph theoretic setting where the labels are assigned based...
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