Trash screen blockage detection using cameras and deep learning: code and dataset

How to cite this Dataset

Vandaele, Remy (2023): Trash screen blockage detection using cameras and deep learning: code and dataset. University of Reading. Dataset. https://doi.org/10.17864/1947.000498

Description

This dataset provides access to the images and network weights produced during our research on trash screen detection, along with minimum working examples allowing to use the network weights on new trash screen camera images. The images come from 54 different cameras with open access feeds provided by the Environment Agency (http://eadevonwebcams.org.uk/), and were collected from January 2022 to January 2023. The images were manually annotated with a "clear" (if the trash screen looks clear), "blocked" (if the trash screen looks blocked) or "other" (if unsure) label. The network weights and minimum working examples allow to estimate labels of new trash screen images using three different methods: a classifier, a siamese network and an anomaly detection method.

Resource Type:

Dataset

Creators:

Vandaele, Remy

Contributors:

Dance, Sarah