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

Inference of Convolutional Neural Networks in time critical applicationsusually requires a GPU. In robotics or embedded devices these are often notavailable due to energy, space and cost constraints. Furthermore, installationof a deep learning framework or even a native compiler on the target platformis not possible. This paper presents a neural network code generator (NNCG)that generates from a trained CNN a plain ANSI C code file that encapsulatesthe inference in single a function. It can easily be included in existingprojects and due to lack of dependencies, cross compilation is usuallypossible. Additionally, the code generation is optimized based on the knowntrained CNN and target platform following four design principles. The system isevaluated utilizing small CNN designed for this application. Compared toTensorFlow XLA and Glow speed-ups of up to 11.81 can be shown and even GPUs areoutperformed regarding latency.

A C Code Generator for Fast Inference and Simple Deployment of Convolutional Neural Networks on Resource Constrained Systems