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Claims › ext:c6e218b86f48630d › line of work

Its line of work

But more importantly, it yields consistent and significant boosts in detection performance on benchmarks like PASCAL VOC 2007 and 2012.

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 ScienceBut more importantly, it yields consistent and significant boosts in detection performance on benchmarks like PASCAL VO… takes its method from Fast R-CNN trains the very deep VGG16 network 9x faster than R-CNN, is 213x faster at test-time, and achieves a higher… (identified in the literature)Fast R-CNN trains the very deep VGG16 network 9x faster than R-CNN, is 213x faster at test-time, and achieves a higher…: unchecked, credence 0.55, stakes 16.4, reliance 2.0Fast R-CNN trains the…But more importantly, it yields consistent and significant boosts in detection performance on benchmarks like PASCAL VO…: unchecked, credence 0.55, stakes 11.4But more importantly…

● established◐ supported○ unchecked◆ contested✕ refuted⊘ tried, not checkable

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 16.4 the claim it is drawn around

The drawing is wider than this screen: drag it sideways to see the rest, or read the table.

Every claim drawn, as a table
ClaimStatusCheckableCredenceUseStakesRests on
Fast R-CNN trains the very deep VGG16 network 9x faster than R-CNN, is 213x faster at test-time, and achieves a higher…○ uncheckedyes0.55016.4—
But more importantly, it yields consistent and significant boosts in detection performance on benchmarks like PASCAL VO…○ uncheckedyes0.55011.4Fast R-CNN trains the very deep VGG16 network 9x faster than R-CNN, is 213x faster at test-time, and achieves a higher…

See its whole group in the network, where it can be filtered and sized.

Step by step

WhereStatusClaimCredence
1 step belowuncheckedFast R-CNN trains the very deep VGG16 network 9x faster than R-CNN, is 213x faster at test-time, and achieves a higher mAP on PASCAL VOC 2012.this claim takes its method from it, as the citing paper says · human literature · ext:a2c06ad4ea7aa19b0.55
this claimuncheckedBut more importantly, it yields consistent and significant boosts in detection performance on benchmarks like PASCAL VOC 2007 and 2012.human literature · ext:c6e218b86f48630d0.55

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