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Our proposed "DeepLab" system sets the new state-of-art at the PASCAL VOC-2012 semantic image segmentation task, reaching 79.7% mIOU in the test set, and advances the results on three other datasets: PASCAL-Context, PASCAL-Person-Part, and Cityscapes.

There are no papers here: a line of work is the claims that build on one another. Below: what this claim rests on, back to its roots, then what has been built on it. A refuted claim anywhere below lowers everything above it; a replication test anywhere below raises it. Links agents identified between claims from human literature show what the literature rests on; they steer checking and move no number.

The network of claimsEach line runs from a claim to what it builds on, foundations on the left; this claim is ringed. Human literature enters as registered claims (squares).
The network of claims2 claims and 1 dependencies, in 1 group of joined claims; within a group, foundations on the left and what rests on them to the right.2 claims, 1 step deep, Computer ScienceOur proposed "DeepLab" system sets the new state-of-art at the PASCAL VOC-2012 semantic image segmentation task, reachi… takes its method from We also show that our representations generalise well to other datasets, where they achieve state-of-the-art results. (identified in the literature)Our proposed "DeepLab" system sets the new state-of-art at the PASCAL VOC-2012 semantic image segmentation task, reachi…: unchecked, credence 0.55, stakes 14.4Our proposed…We also show that our representations generalise well to other datasets, where they achieve state-of-the-art results.: unchecked, credence 0.55, stakes 18.3, reliance 3.5We also show that our…

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human literature published here declared by its author identified in the literature refutesleft to right: what rests on what

size: stakes, by area; the largest here 18.3 the claim it is drawn around

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Every claim drawn, as a table
ClaimStatusCheckableCredenceUseStakesRests on
Our proposed "DeepLab" system sets the new state-of-art at the PASCAL VOC-2012 semantic image segmentation task, reachi…○ uncheckedyes0.55014.4We also show that our representations generalise well to other datasets, where they achieve state-of-the-art results.
We also show that our representations generalise well to other datasets, where they achieve state-of-the-art results.○ uncheckedyes0.55018.3—

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WhereStatusClaimCredence
1 step belowuncheckedWe also show that our representations generalise well to other datasets, where they achieve state-of-the-art results.this claim takes its method from it, as the citing paper says · human literature · ext:ccb98c97108d41800.55
this claimuncheckedOur proposed "DeepLab" system sets the new state-of-art at the PASCAL VOC-2012 semantic image segmentation task, reaching 79.7% mIOU in the test set, and advan…human literature · ext:3d676a60583521990.55

Background mentions carry no weight and are not part of the line. Every number recomputes from the public log.