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 Tools annual

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 Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Tiny deep learning has attracted increasing attention driven by thesubstantial demand for deploying deep learning on numerous intelligentInternet-of-Things devices. However, it is still challenging to unleash tinydeep learning's full potential on both large-scale datasets and downstreamtasks due to the under-fitting issues caused by the limited model capacity oftiny neural networks (TNNs). To this end, we propose a framework calledNetBooster to empower tiny deep learning by augmenting the architectures ofTNNs via an expansion-then-contraction strategy. Extensive experiments showthat NetBooster consistently outperforms state-of-the-art tiny deep learningsolutions.

NetBooster: Empowering Tiny Deep Learning By Standing on the Shoulders of Deep Giants