English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Inspired by the ConvNets with structured hidden representations, we propose aTensor-based Neural Network, TCNN. Different from ConvNets, TCNNs are composedof structured neurons rather than scalar neurons, and the basic operation isneuron tensor transformation. Unlike other structured ConvNets, where thepart-whole relationships are modeled explicitly, the relationships are learnedimplicitly in TCNNs. Also, the structured neurons in TCNNs are high-ranktensors rather than vectors or matrices. We compare TCNNs with current popularConvNets, including ResNets, MobileNets, EfficientNets, RegNets, etc., onCIFAR10, CIFAR100, and Tiny ImageNet. The experiment shows that TCNNs havehigher efficiency in terms of parameters. TCNNs also show higher robustnessagainst white-box adversarial attacks on MNIST compared to ConvNets.

A Tensor-based Convolutional Neural Network for Small Dataset Classification