Methods › Computer Vision › Light-weight neural networks › MobileNetV1 › Papers where code ran, page 1
MobileNetV1
Papers archive 2025-07-28
archive papers tagged: 74 · with a code link: 43 · where Syntology ran a sample: 15 (13 with a run with no instrument failure, 2 where every run was a failure of Syntology's instrument) Syntology
Show: all tagged papersonly where code ran (15 of 74 tagged: 13 with a run with no instrument failure, 2 where every run was a failure of Syntology's instrument)
Syntology We ran code from the paper's repository; we did not isolate this method inside it.
Page 1 of 1: papers 1 to 15 of the 15 tagged papers where Syntology ran at least one harvested sample (13 with a run with no instrument failure, 2 where every run was a failure of Syntology's instrument), newest first by the archive's date (ties by arXiv id). This is a filter on Syntology's record ordered by date only, not a ranking; a run is not a correctness claim. A paper missing from this list is not a recorded non-run: it may have no arXiv id, no harvested code, or only samples that have not run yet.
Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code, as “N ran (of which C constructed an object rather than computing a result; K with no instrument failure: H honoured, V violated, P with no contract checked; I where Syntology's instrument failed) · U unverified”; the instrument figure counts failures of Syntology's instrument, not of the code. It is per sample and not a correctness claim. When the archive marks a repository official for the paper, the line starts with that repository's state (the archive's flag, not a verdict on who wrote the code; “community repositories only” when every sample that ran came from a community repository, “official: no sample here; runs from other or unrecorded repositories” when some came from a repository the paper names or has in its text, or from none recorded); hover it for the repositories the samples that ran came from.
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SWAP: Sparse Entropic Wasserstein Regression for Robust Network Pruning 7 Oct 2023 · 1 repository · arXiv:2310.04918Syntology official (archive's flag): 5 ran · 5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified (of 5 harvested samples) · 5 pointer-only (licence)
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MobileStereoNet: Towards Lightweight Deep Networks for Stereo Matching 22 Aug 2021 · 4 repositories · arXiv:2108.09770Syntology official (archive's flag): 1 ran · 8 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified (of 8 harvested samples)
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Towards Fast, Accurate and Stable 3D Dense Face Alignment 21 Sep 2020 · 3 repositories · arXiv:2009.09960Syntology official (archive's flag): 7 ran · 9 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 1 honoured, 1 violated, 3 with no contract checked; 4 where Syntology's instrument failed) · 1 unverified (of 10 harvested samples) · 7 pointer-only (licence)
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EagleEye: Fast Sub-net Evaluation for Efficient Neural Network Pruning 6 Jul 2020 · 1 repository · arXiv:2007.02491Syntology official (archive's flag): 3 ran · 3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified (of 4 harvested samples) · 4 pointer-only (licence)
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Soft Threshold Weight Reparameterization for Learnable Sparsity 8 Feb 2020 · 1 repository · arXiv:2002.03231Syntology official (archive's flag): 1 ran · 1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified (of 3 harvested samples) · 1 pointer-only (licence)
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Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network 17 Jan 2020 · 1 repository · arXiv:2001.06268Syntology official (archive's flag): 3 ran · 3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 8 unverified (of 11 harvested samples)
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Discrimination-aware Network Pruning for Deep Model Compression 4 Jan 2020 · 1 repository · arXiv:2001.01050Syntology official (archive's flag): 2 ran · 2 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified (of 4 harvested samples)
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Mish: A Self Regularized Non-Monotonic Activation Function 23 Aug 2019 · 9 repositories · arXiv:1908.08681Syntology official (archive's flag): 6 ran · 9 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 1 honoured, 0 violated, 7 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified (of 12 harvested samples) · 1 pointer-only (licence)
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MixConv: Mixed Depthwise Convolutional Kernels 22 Jul 2019 · 13 repositories · arXiv:1907.09595Syntology community repositories only · 2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified (of 3 harvested samples) · 1 pointer-only (licence)
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Memory-Driven Mixed Low Precision Quantization For Enabling Deep Network Inference On Microcontrollers 30 May 2019 · 2 repositories · arXiv:1905.13082Syntology official (archive's flag): 4 ran · 4 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified (of 4 harvested samples) · 4 pointer-only (licence)
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Slimmable Neural Networks 21 Dec 2018 · 4 repositories · arXiv:1812.08928Syntology official (archive's flag): 2 ran · 2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 2 harvested samples) · 2 pointer-only (licence)
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CBAM: Convolutional Block Attention Module 17 Jul 2018 · 31 repositories · arXiv:1807.06521Syntology 13 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 1 honoured, 0 violated, 9 with no contract checked; 3 where Syntology's instrument failed) · 9 unverified (of 22 harvested samples) · 3 pointer-only (licence)
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NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications 9 Apr 2018 · 4 repositories · arXiv:1804.03230Syntology 1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 1 harvested sample) · 1 pointer-only (licence)
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Receptive Field Block Net for Accurate and Fast Object Detection 21 Nov 2017 · 7 repositories · arXiv:1711.07767Syntology official: no sample here; runs from other or unrecorded repositories · 3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified (of 3 harvested samples) · 3 pointer-only (licence)
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MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications 17 Apr 2017 · 159 repositories · arXiv:1704.04861Syntology official: no sample here; runs from other or unrecorded repositories · 53 ran (of which 28 constructed an object rather than computing a result; 44 with no instrument failure: 4 honoured, 0 violated, 40 with no contract checked; 9 where Syntology's instrument failed) · 30 unverified (of 83 harvested samples) · 48 pointer-only (licence)