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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

recognition system from PDF files is a relatively young research field where techniques and algorithms are proposed to identify type of charts and interpret them. This paper focus on recognition of chart type that is a part of PDF document using texture features and classification algorithm. Eleven types of texture features and three classifiers, namely, Multilayer perceptron, support vector machine and K nearest neighbour, are used. Performance analysis of the proposed chart type recognition systems show that texture features for chart type recognition has promising future and produces best result while using KNN and SVM algorithm.

Machine Learning Classification Algorithms to Recognize Chart Types in Portable Document Format (PDF) Files