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Inception-v3 Module

95 papers tagged archive 2025-07-28

Introduced by Christian Szegedy et al. in Rethinking the Inception Architecture for Computer Vision

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Inception-v3 Module is an image block used in the Inception-v3 architecture. This architecture is used on the coarsest (8 × 8) grids to promote high dimensional representations.

PaperSourceSee Code · pytorch/vision

Papers archive 2025-07-28

30 shown of 95, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 99 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Image Classification17
Transfer Learning17
General Classification15
Classification13
image-classification10
Deep Learning9
Adversarial Attack6
Quantization4
Diagnostic3
Diversity3
Image Captioning3
Image Generation3
Management3
Object Detection3
Prediction3
Semantic Segmentation3
object-detection3
BIG-bench Machine Learning2
Benchmarking2
Binary Classification2

Usage over time archive 2025-07-28

Papers per year tagged with Inception-v3 Module: 2015 to 2025, peak 21 21 0 2015: 1 paper 2015 2016: 2 papers 2016 2017: 5 papers 2017 2018: 13 papers 2018 2019: 15 papers 2019 2020: 21 papers 2020 2021: 11 papers 2021 2022: 10 papers 2022 2023: 8 papers 2023 2024: 5 papers 2024 2025: 4 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (95 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Image Model Blocks

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