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      "statement": "# GoogLeNet/Inception: multi-scale branches with bottleneck projections\n\nCombined parallel convolution/pooling branches and1×1channel-reduction projections in repeated Inception modules, balancing network width/depth and computation in GoogLeNet.\n\n## Scientific scope\n\nDistinct from formal Inception-v3's later factorization/regularization refinements. Inherits NetworkInNetwork1×1convolutions and prior multi-scale reasoning; source explicitly treats its sparse/Hebbian design motivation as unverified, not a proved automatic optimal architecture.22layer entry and ensemble gains are benchmark/protocol specific.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\nChristian Szegedy; Wei Liu; Yangqing Jia; Pierre Sermanet; Scott Reed; Dragomir Anguelov; Dumitru Erhan; Vincent Vanhoucke; Andrew Rabinovich\n\nSource-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.\n\n\n\n## Original sources\n\n- [Going Deeper with Convolutions](https://arxiv.org/abs/1409.4842v1)\n",
      "summary": "Combined parallel convolution/pooling branches and1×1channel-reduction projections in repeated Inception modules, balancing network width/depth and computation in GoogLeNet.",
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