Unverified70% confidenceFactExact time
InceptionV1 (GoogLeNet) is an early deep convolutional network proposed by Google in 2014, whose Inception module improves feature extraction efficiency by using convolutional kernels of different sizes in parallel.
2
Sources
70%
Confidence
Long-term
Relevance
7/16/2026
First Seen
Sources
Related Claims
UnverifiedInception V1 is a classic convolutional network proposed by Google in 2014 and, due to its breakthrough on ImageNet and its compact structure, has long been the "fruit fly" model for interpretability research; its conv5-1 layer has 480 channels and was systematically studied by Olah et al. using feature visualization.78% similarVerifiedCloud computing vendors such as AWS and Google Cloud have already introduced Spot Instance and reserved instance mechanisms.63% similarUnverifiedGoogle has released EmbeddingGemma 2, an embedding model with a total of 740M parameters, which is Google's first natively multimodal on-device open-source embedding model.63% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/530591API
curl https://kongchang.com/api/v1/knowledge/claims/530591MCP
get_claim(id=530591)