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/

Zendy Plus

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

Zendy Tools

Zendy Open

This study attempts to provide explanations, descriptions and evaluations ofsome most popular and current combinations of description and descriptorframeworks, namely SIFT, SURF, MSER, and BRISK for keypoint extractors andSIFT, SURF, BRISK, and FREAK for descriptors. Evaluations are made based on thenumber of matches of keypoints and repeatability in various image variations.It is used as the main parameter to assess how well combinations of algorithmsare in matching objects with different variations. There are many papers thatdescribe the comparison of detection and description features to detect objectsin images under various conditions, but the combination of algorithms attachedto them has not been much discussed. The problem domain is limited to differentillumination levels and affine transformations from different perspectives. Toevaluate the robustness of all combinations of algorithms, we use a stereoimage matching case.

Evaluation of Feature Detector-Descriptor for Real Object Matching under Various Conditions of Ilumination and Affine Transformation