Historical context & research account
LeNet-5 and related work integrate convolution, shared weights and gradient-based training into a stable visual architecture. Later developments including AlexNet, convolutional encoders in generative models and visual feature extraction inherit elements of this tradition. The node documents technical conditions for subsequent visual learning.
Dates & version record
Date displayed for this node：1998 · Date recorded in the research master：1998
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Original sources & further reading
These links lead to the cited paper, article, institution or conference page. External texts retain their source languages.
Gradient-Based Learning Applied to Document Recognition
https://doi.org/10.1109/5.726791
Current cited URL
Provenance, translation & verification
Archive node #036 · Historical node
Research masters & supplement references · 1
AI Art Genealogy Research Master · p. 13 · 036
Date as recorded: 1998
Gradient-Based Learning Applied to Document Recognition ↗
Gradient-Based Learning Applied to Document Recognition
Archive account adapted from the masters, not a full translation of the linked work. AI-assisted translation; human review pending.
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Cite this node
ANTI-AI ARCHIVE. Gradient-Based Learning Applied to Document Recognition. Art-history node #036. https://salondesrefuses.cn/en/art-history/036
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