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

Tiger conservation necessitates the strategic deployment of multifacetedinitiatives encompassing the preservation of ecological habitats, anti-poachingmeasures, and community involvement for sustainable growth in the tigerpopulation. With the advent of artificial intelligence, tiger surveillance canbe automated using object detection. In this paper, an accurate illuminationinvariant framework is proposed based on EnlightenGAN and YOLOv8 for tigerdetection. The fine-tuned YOLOv8 model achieves a mAP score of 61% withoutillumination enhancement. The illumination enhancement improves the mAP by0.7%. The approaches elevate the state-of-the-art performance on the ATRWdataset by approximately 6% to 7%.

An Efficient Illumination Invariant Tiger Detection Framework for Wildlife Surveillance