Contains data and code to support the submission of " Automated river plastic monitoring using deep learning and cameras" on 06-05-202
This release accompanies the publication of: Valero, D., Belay, B.S., Moreno-Rodenas, A., Kramer, M....
The interest in visual-based surveillance systems, especially in natural disaster applications, such...
We investigate a deep transfer learning methodology to perform water segmentation and water level pr...
Quantifying plastic pollution on surface water is essential to understand and mitigate the impact of...
Floods are major natural disasters which cause deaths and material damages every year. Monitoring th...
This dataset contains: - The networks weights (weights.zip) that were obtained and used in our pap...
Plastic pollution is one of the most challenging global environmental problems. Currently, more than...
This package provides material that can be openly published for the paper "Scalable Flood Level Tren...
Plastic pollution in water bodies is an unresolved environmental issue that damages all aquatic envi...
This package provides material that can be openly published for the paper "Scalable Flood Level Tren...
Plastic pollution in the sea is an environmental hazard, negatively impacts marine life, and causes ...
The accumulation of plastic objects in the Earth’s environment will adversely affect wildlife, wildl...
This repository contains the code and database used in the paper 'Convolutional neural networks faci...
Water is an indispensable resource on Earth for many tasks. For some applications, the quality of th...
Deep Plastic Enhanced Object Detection for Epipelagic Plastic. This repository contains source c...
This release accompanies the publication of: Valero, D., Belay, B.S., Moreno-Rodenas, A., Kramer, M....
The interest in visual-based surveillance systems, especially in natural disaster applications, such...
We investigate a deep transfer learning methodology to perform water segmentation and water level pr...
Quantifying plastic pollution on surface water is essential to understand and mitigate the impact of...
Floods are major natural disasters which cause deaths and material damages every year. Monitoring th...
This dataset contains: - The networks weights (weights.zip) that were obtained and used in our pap...
Plastic pollution is one of the most challenging global environmental problems. Currently, more than...
This package provides material that can be openly published for the paper "Scalable Flood Level Tren...
Plastic pollution in water bodies is an unresolved environmental issue that damages all aquatic envi...
This package provides material that can be openly published for the paper "Scalable Flood Level Tren...
Plastic pollution in the sea is an environmental hazard, negatively impacts marine life, and causes ...
The accumulation of plastic objects in the Earth’s environment will adversely affect wildlife, wildl...
This repository contains the code and database used in the paper 'Convolutional neural networks faci...
Water is an indispensable resource on Earth for many tasks. For some applications, the quality of th...
Deep Plastic Enhanced Object Detection for Epipelagic Plastic. This repository contains source c...
This release accompanies the publication of: Valero, D., Belay, B.S., Moreno-Rodenas, A., Kramer, M....
The interest in visual-based surveillance systems, especially in natural disaster applications, such...
We investigate a deep transfer learning methodology to perform water segmentation and water level pr...
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