Results 231 to 240 of about 4,414 (249)
Some of the next articles are maybe not open access.
Detecting Floating Macroplastic Litter with Semi-Supervised Deep Learning
Researchers are increasingly utilizing Deep Learning methods for computer vision to identify and quantify floating macroplastic litter. While these methods can provide precise assessments of plastic pollution by automatically processing images and videos, they often rely on the availability of large amount of annotated data for supervised learning (SL).Tianlong Jia +3 more
openaire +1 more source
Environmental and socioeconomic factors impacting floating litter loading in streams
Freshwater litter is an increasing environmental and economic concern, yet it remains less studied than marine debris despite its role as a pathway to ocean systems. This study quantified floating litter loading and evaluated the influence of watershed characteristics across 30 in-stream litter collection devices distributed throughout the southeasternElinor R. Mallon +5 more
openaire +1 more source
Visualization products for floating micro-litter data
Gaudin, François +10 moreopenaire +1 more source