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Identifying Table Structure in Documents using Conditional Generative Adversarial Networks
In many industries, as well as in academic research, information is primarily transmitted in the form of unstructured documents (this article, for example).
Generative Adversarial Network
Small Data Image Classification
Extracting Tables from Documents using Conditional Generative Adversarial Networks and Genetic Algorithms
Our proposed method takes a top-down approach, first using a generative adversarial network to map a table image into a standardised `skeleton' table form denoting the approximate row and column borders without table content, then fitting renderings of candidate latent table structures to the skeleton structure using a distance measure optimised by a genetic algorithm.
Synaptic Scaling Balances Learning in a Spiking Model of Neocortex
Learning in the brain requires complementary mechanisms: potentiation and activity-dependent homeostatic scaling.
