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

This work presents the Industrial Hand Action Dataset V1, an industrialassembly dataset consisting of 12 classes with 459,180 images in the basicversion and 2,295,900 images after spatial augmentation. Compared to otherfreely available datasets tested, it has an above-average duration and, inaddition, meets the technical and legal requirements for industrial assemblylines. Furthermore, the dataset contains occlusions, hand-object interaction,and various fine-grained human hand actions for industrial assembly tasks thatwere not found in combination in examined datasets. The recorded ground truthassembly classes were selected after extensive observation of real-world usecases. A Gated Transformer Network, a state-of-the-art model from thetransformer domain was adapted, and proved with a test accuracy of 86.25%before hyperparameter tuning by 18,269,959 trainable parameters, that it ispossible to train sequential deep learning models with this dataset.

Challenges of the Creation of a Dataset for Vision Based Human Hand Action Recognition in Industrial Assembly