Bibliographies

Jakovljevic, G., Govedarica, M., and Alvarez-Taboada, F.(2020). A deep learning model for automatic plastic mapping using unmanned aerial vehicle (UAV) data, Remote Sens. (Basel), 12, 1515 ( [...]

Hengstmann, E., Gräwe, D., Tamminga, M., and Fischer, E. K.(2017). Marine litter abundance and distribution on beaches on the Isle of Rügen considering the influence of exposition, morphology and [...]

Ge, Z., Shi, H., Mei, X., Dai, Z., and Li, D. (2016).  Semi-automatic recognition of marine debris on beaches, Sci. Rep., 6, 25759, https://doi.org/10.1038/srep25759.

Garcia-Garin, O., Monleón-Getino, T., López-Brosa, P., Borrell, A., Aguilar, A., Borja-Robalino, R., Cardona, L., and Vighi, M. (2021). Automatic detection and quantification of floating marine [...]

Garcia-Garin, O., Aguilar, A., Borrell, A., Gozalbes, P., Lobo, A., Penadés-Suay, J., Raga, J. A., Revuelta, O., Serrano, M., and Vighi, M. (2020). Who’s better at spotting? A comparison between [...]

Geraeds, M.; van Emmerik, T.; de Vries, R. and bin Ab Razak, M.S. (2019). Riverine Plastic Litter Monitoring Using Unmanned Aerial Vehicles (UAVs). Remote Sens. 11, 2045, [...]

Fallati, L., Polidori, A., Salvatore, C., Saponari, L., Savini, A., and Galli, P.(2019). Anthropogenic marine debris assessment with unmanned aerial vehicle imagery and deep learning: A case [...]

Deidun, A., Gauci, A., Lagorio, S., and Galgani, F. (2018).  Optimising beached litter monitoring protocols through aerial imagery, Mar. Pollut. Bull., 131, 212-217, [...]

Balsi, M., Moroni, M., Chiarabini, V., and Tanda, G.(2021). High-resolution aerial detection of marine plastic litter by hyperspectral sensing, Remote Sens. (Basel), 13, 1557, [...]

Aoyama, T. (2016). Extraction of marine debris in the Sea of Japan using satellite images, Proc. SPIE 9878, Remote Sensing of the Oceans and Inland Waters: Techniques, Applications, and [...]