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

Traffic light detection is a challenging problem in the context ofself-driving cars and driver assistance systems. While most existing systemsproduce good results on large traffic lights, detecting small and tiny ones isoften overlooked. A key problem here is the inherent downsampling in CNNs,leading to low-resolution features for detection. To mitigate this problem, wepropose a new traffic light detection system, comprising a novel traffic lightproposal generator that utilizes findings from general object proposalgeneration, fine-grained multi-scale features, and attention for efficientprocessing. Moreover, we design a new detection head for classifying andrefining our proposals. We evaluate our system on three challenging, publiclyavailable datasets and compare it against six methods. The results showsubstantial improvements of at least $12.6\%$ on small and tiny traffic lights,as well as strong results across all sizes of traffic lights.

Small, but important: Traffic light proposals for detecting small traffic lights and beyond