Matches in Nanopublications for { ?s <http://schema.org/description> ?o ?g. }
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- 2114 description "" assertion.
- d2838de8-72fc-4d17-83c3-fed943ac78f0 description "Hypermatrix size 2x2 blocks, block size 2x2 elements" assertion.
- d2838de8-72fc-4d17-83c3-fed943ac78f0 description "Hypermatrix size 2x2 blocks, block size 2x2 elements" assertion.
- d2838de8-72fc-4d17-83c3-fed943ac78f0 description "Darwin MacBook-Pro-Raul-2025.local 24.5.0 Darwin Kernel Version 24.5.0: Tue Apr 22 19:53:27 PDT 2025; root:xnu-11417.121.6~2/RELEASE_ARM64_T6041 arm64" assertion.
- d2838de8-72fc-4d17-83c3-fed943ac78f0 description "Darwin MacBook-Pro-Raul-2025.local 24.5.0 Darwin Kernel Version 24.5.0: Tue Apr 22 19:53:27 PDT 2025; root:xnu-11417.121.6~2/RELEASE_ARM64_T6041 arm64" assertion.
- 2bf76bb0-6372-4405-9fcd-f234b29bbde7 description "Auxiliary File" assertion.
- 2bf76bb0-6372-4405-9fcd-f234b29bbde7 description "Auxiliary File" assertion.
- 5d13adf7-6c35-4853-9863-5ed0de3ecc20 description "COMPSs application Tasks profile" assertion.
- 5d13adf7-6c35-4853-9863-5ed0de3ecc20 description "COMPSs application Tasks profile" assertion.
- 613717b6-a0dc-45df-88c5-71c7b4122b3d description "COMPSs Workflow Provenance YAML configuration file" assertion.
- 613717b6-a0dc-45df-88c5-71c7b4122b3d description "COMPSs Workflow Provenance YAML configuration file" assertion.
- 900f6b13-e6e0-42f0-914a-e0c767828c40 description "COMPSs submission command line (runcompss / enqueue_compss), including flags and parameters passed to the application" assertion.
- 900f6b13-e6e0-42f0-914a-e0c767828c40 description "COMPSs submission command line (runcompss / enqueue_compss), including flags and parameters passed to the application" assertion.
- 995655f1-39da-415e-bd65-3ee2c08aa027 description "Main file of the COMPSs workflow source files" assertion.
- 995655f1-39da-415e-bd65-3ee2c08aa027 description "Main file of the COMPSs workflow source files" assertion.
- f5cf6566-7ce3-40a3-a8ec-b1d96689b850 description "The graph diagram of the workflow, automatically generated by COMPSs runtime" assertion.
- f5cf6566-7ce3-40a3-a8ec-b1d96689b850 description "The graph diagram of the workflow, automatically generated by COMPSs runtime" assertion.
- 59d47b38-91be-4eb2-9a4c-a2b3bd3ba5a7 description "Hypermatrix size 2x2 blocks, block size 2x2 elements" assertion.
- 59d47b38-91be-4eb2-9a4c-a2b3bd3ba5a7 description "Hypermatrix size 2x2 blocks, block size 2x2 elements" assertion.
- 019c504a-dce8-4969-be12-9558468be248 description "Auxiliary File" assertion.
- 019c504a-dce8-4969-be12-9558468be248 description "Auxiliary File" assertion.
- 6a5db15c-4b0a-4146-a393-cd5d00f281db description "COMPSs Workflow Provenance YAML configuration file" assertion.
- 6a5db15c-4b0a-4146-a393-cd5d00f281db description "COMPSs Workflow Provenance YAML configuration file" assertion.
- 85e21e00-ba4d-41ab-a4a6-ab9521068de5 description "The graph diagram of the workflow, automatically generated by COMPSs runtime" assertion.
- 85e21e00-ba4d-41ab-a4a6-ab9521068de5 description "The graph diagram of the workflow, automatically generated by COMPSs runtime" assertion.
- 8e897b78-2a9e-4648-9561-b80167c6043a description "COMPSs application Tasks profile" assertion.
- 8e897b78-2a9e-4648-9561-b80167c6043a description "COMPSs application Tasks profile" assertion.
- b08f5831-1d9f-4190-8497-f9aa5f399e22 description "COMPSs submission command line (runcompss / enqueue_compss), including flags and parameters passed to the application" assertion.
- b08f5831-1d9f-4190-8497-f9aa5f399e22 description "COMPSs submission command line (runcompss / enqueue_compss), including flags and parameters passed to the application" assertion.
- b4a0b545-8c0c-4b67-9b0a-7ed7faa17aaf description "Main file of the COMPSs workflow source files" assertion.
- b4a0b545-8c0c-4b67-9b0a-7ed7faa17aaf description "Main file of the COMPSs workflow source files" assertion.
- environment.lock.yml description "Python environment for executing the associated Jupyter notebook." assertion.
- environment.lock.yml description "Python environment for executing the associated Jupyter notebook." assertion.
- environment.lock.yml description "Python environment for executing the associated Jupyter notebook." assertion.
- environment.lock.yml description "Python environment for executing the associated Jupyter notebook." assertion.
- environment.yml description "environment.yml (Conda environment for Python JupyterGIS)" assertion.
- environment.yml description "environment.yml (Conda environment for Python JupyterGIS)" assertion.
- environment.yml description "environment.yml (Conda environment for Python JupyterGIS)" assertion.
- environment.yml description "environment.yml (Conda environment for Python JupyterGIS)" assertion.
- get_typename_from_WFS.ipynb description "## Get data layer names from WFS service URL **Learn how to get the typename (e.g. data layers) which are requested for querying WFS services**" assertion.
- get_typename_from_WFS.ipynb description "## Get data layer names from WFS service URL **Learn how to get the typename (e.g. data layers) which are requested for querying WFS services**" assertion.
- get_typename_from_WFS.ipynb description "## Get data layer names from WFS service URL **Learn how to get the typename (e.g. data layers) which are requested for querying WFS services**" assertion.
- get_typename_from_WFS.ipynb description "## Get data layer names from WFS service URL **Learn how to get the typename (e.g. data layers) which are requested for querying WFS services**" assertion.
- saarland-flooding description "Jupyter Book (HTML rendered version) to showcase JupyterGiS in action using flooding event data from Saarland, Germany, available via the Urban Data Portal." assertion.
- saarland-flooding description "Jupyter Book (HTML rendered version) to showcase JupyterGiS in action using flooding event data from Saarland, Germany, available via the Urban Data Portal." assertion.
- saarland-flooding description "Jupyter Book (HTML rendered version) to showcase JupyterGiS in action using flooding event data from Saarland, Germany, available via the Urban Data Portal." assertion.
- saarland-flooding description "Jupyter Book (HTML rendered version) to showcase JupyterGiS in action using flooding event data from Saarland, Germany, available via the Urban Data Portal." assertion.
- zenodo.15470110 description "Saarland flooding (Galaxy History) with outputs and executed notebooks." assertion.
- zenodo.15470110 description "Saarland flooding (Galaxy History) with outputs and executed notebooks." assertion.
- zenodo.15470110 description "Saarland flooding (Galaxy History) with outputs and executed notebooks." assertion.
- zenodo.15470110 description "Saarland flooding (Galaxy History) with outputs and executed notebooks." assertion.
- saarland-flooding.git description "This Github repository contains the latest version of the jupyter notebooks showcasing JupyterGIS." assertion.
- saarland-flooding.git description "This Github repository contains the latest version of the jupyter notebooks showcasing JupyterGIS." assertion.
- saarland-flooding.git description "This Github repository contains the latest version of the jupyter notebooks showcasing JupyterGIS." assertion.
- saarland-flooding.git description "This Github repository contains the latest version of the jupyter notebooks showcasing JupyterGIS." assertion.
- document description "The multiplication of publicly available datasets makes it possible to develop Deep Learning models for many real-world applica tions. However, some domains are still poorly explored, and their related datasets are often small or inconsistent. In addition, some biases linked to the dataset construction or labeling may give the impression that a model is particularly efficient. Therefore, evaluating a model requires a clear understanding of the database. Moreover, a model often reflects a given dataset’s performance and may deteriorate if a shift exists between the training dataset and real-world data. In this paper, we derive a more consistent and balanced version of the TrashCan [6] image dataset, called UNO, to evaluate models for de tecting non-natural objects in the underwater environment. We pro pose a method to balance the number of annotations and images for cross-evaluation. We then compare the performance of a SOTA object detection model when using TrashCAN and UNO datasets. Addition ally, we assess covariate shift by testing the model on an image dataset for real-world application. Experimental results show significantly better and more consistent performance using the UNO dataset. The UNO database and the code are publicly av https://github.com/CBarrelet/balanced_kfold" assertion.
- document description "The multiplication of publicly available datasets makes it possible to develop Deep Learning models for many real-world applica tions. However, some domains are still poorly explored, and their related datasets are often small or inconsistent. In addition, some biases linked to the dataset construction or labeling may give the impression that a model is particularly efficient. Therefore, evaluating a model requires a clear understanding of the database. Moreover, a model often reflects a given dataset’s performance and may deteriorate if a shift exists between the training dataset and real-world data. In this paper, we derive a more consistent and balanced version of the TrashCan [6] image dataset, called UNO, to evaluate models for de tecting non-natural objects in the underwater environment. We pro pose a method to balance the number of annotations and images for cross-evaluation. We then compare the performance of a SOTA object detection model when using TrashCAN and UNO datasets. Addition ally, we assess covariate shift by testing the model on an image dataset for real-world application. Experimental results show significantly better and more consistent performance using the UNO dataset. The UNO database and the code are publicly av https://github.com/CBarrelet/balanced_kfold" assertion.
- 13952176 description "Three underwater macro-litter image datasets for object detection in YOLO format: UNO dataset: All details are available in From TrashCan to UNO: Deriving an Underwater Image Dataset to Get a More Consistent and Balanced Version, C.Barrelet et al, ICPR 2022 MORGANE dataset: Images taken in shallow water in the harbors near Montpellier, France VENICE dataset: Images taken during the MAELSTROM experiments in Venice, Italy" assertion.
- 13952176 description "Three underwater macro-litter image datasets for object detection in YOLO format: UNO dataset: All details are available in From TrashCan to UNO: Deriving an Underwater Image Dataset to Get a More Consistent and Balanced Version, C.Barrelet et al, ICPR 2022 MORGANE dataset: Images taken in shallow water in the harbors near Montpellier, France VENICE dataset: Images taken during the MAELSTROM experiments in Venice, Italy" assertion.
- 14929590 description "Petrizzo, A., MOSCHINO, V., Madricardo, F., Ghezzo, M., Galvez, D., Rodriguez, M., & ferrari, . nicola . (2022). D5.1 Report on site identification and installation of the Seabed Cleaning System in Venice. MAELSTROM Project. https://doi.org/10.5281/zenodo.14929590" assertion.
- 14929590 description "Petrizzo, A., MOSCHINO, V., Madricardo, F., Ghezzo, M., Galvez, D., Rodriguez, M., & ferrari, . nicola . (2022). D5.1 Report on site identification and installation of the Seabed Cleaning System in Venice. MAELSTROM Project. https://doi.org/10.5281/zenodo.14929590" assertion.
- 14929678 description "Gouttefarde, M., & Barrelet, C. (2024). D3.3 Preliminary report on the Cable robot autonomous control using Machine learning for litter identification. MAELSTROM Project. https://doi.org/10.5281/zenodo.14929678" assertion.
- 14929678 description "Gouttefarde, M., & Barrelet, C. (2024). D3.3 Preliminary report on the Cable robot autonomous control using Machine learning for litter identification. MAELSTROM Project. https://doi.org/10.5281/zenodo.14929678" assertion.
- 14930072 description "Ehrhorn, P., Iglesias, I., Vieira, L., & Sousa Pinto, I. (2021). D5.3 Definition of location for surface/water column removal device in the Porto region, Portugal. MAELSTROM Project. https://doi.org/10.5281/zenodo.14930072" assertion.
- 14930072 description "Ehrhorn, P., Iglesias, I., Vieira, L., & Sousa Pinto, I. (2021). D5.3 Definition of location for surface/water column removal device in the Porto region, Portugal. MAELSTROM Project. https://doi.org/10.5281/zenodo.14930072" assertion.
- 14931001 description "Rodriguez, M., & Gouttefarde, M. (2022). D3.1 Report on the cable robot design and teleoperated control. MAELSTROM Project. https://doi.org/10.5281/zenodo.14931001" assertion.
- 14931001 description "Rodriguez, M., & Gouttefarde, M. (2022). D3.1 Report on the cable robot design and teleoperated control. MAELSTROM Project. https://doi.org/10.5281/zenodo.14931001" assertion.
- 14931140 description "Gouttefarde, M., & Barrelet, C. (2024). D3.2 Report and videos about the cable robot control with shared autonomy. MAELSTROM Project. https://doi.org/10.5281/zenodo.14931140" assertion.
- 14931140 description "Gouttefarde, M., & Barrelet, C. (2024). D3.2 Report and videos about the cable robot control with shared autonomy. MAELSTROM Project. https://doi.org/10.5281/zenodo.14931140" assertion.
- 15544106 description "Iglesias, I., Vieira, L., Antunes, S., Kett, G., Fantinati, D. del O. A., Nogueira, S., Bio, A., Sousa-Pinto, I., Buschman, F. A., Mira Veiga, J., Pessoa, A., Zingariello, D., & Mule'Stagno, L. (2025). D5.4 Final Report on operation of the surface and water column removal technology in the Porto region. MAELSTROM Project. https://doi.org/10.5281/zenodo.15544106" assertion.
- 15544106 description "Iglesias, I., Vieira, L., Antunes, S., Kett, G., Fantinati, D. del O. A., Nogueira, S., Bio, A., Sousa-Pinto, I., Buschman, F. A., Mira Veiga, J., Pessoa, A., Zingariello, D., & Mule'Stagno, L. (2025). D5.4 Final Report on operation of the surface and water column removal technology in the Porto region. MAELSTROM Project. https://doi.org/10.5281/zenodo.15544106" assertion.
- 15546289 description "Ferrari, N., Fantin, A., Rodríguez Mijangos, M., Sallé, D., Herve, P.-E., Gorrotxategi, J., Oyarzabal, A., Culla, D., Gouttefarde, M., Creuze, V., Barrelet, C., Temperini, H. O., Petrizzo, A., MOSCHINO, V., Mesghez, S., Lahami, T., Lorenzetti, G., & Madricardo, F. (2025). D5.2 Final report on operation of the Seabed Cleaning System in Venice. MAELSTROM Project. https://doi.org/10.5281/zenodo.15546289" assertion.
- 15546289 description "Ferrari, N., Fantin, A., Rodríguez Mijangos, M., Sallé, D., Herve, P.-E., Gorrotxategi, J., Oyarzabal, A., Culla, D., Gouttefarde, M., Creuze, V., Barrelet, C., Temperini, H. O., Petrizzo, A., MOSCHINO, V., Mesghez, S., Lahami, T., Lorenzetti, G., & Madricardo, F. (2025). D5.2 Final report on operation of the Seabed Cleaning System in Venice. MAELSTROM Project. https://doi.org/10.5281/zenodo.15546289" assertion.
- cdd7e89f-7013-45cd-9d15-00c4d7fe19fa description "The robotic seabed cleaning platform developed by TECNALIA, CNRS- LIRMM and “Servizi Tecnici”, consists in a floating platform which, through cables and winches, the seabed cleaning robot is attached. The structure is equipped with a set of sensors for underwater perception to control the robot and detect & identify the marine litter to be removed. Moreover, the robotic platform is characterized by two different tools that allow to collect the ML on the seabed: a drudge to suck up smaller litter and a gripper to grasps larger items like tires, parts of boats, fishing nets etc." assertion.
- cdd7e89f-7013-45cd-9d15-00c4d7fe19fa description "The robotic seabed cleaning platform developed by TECNALIA, CNRS- LIRMM and “Servizi Tecnici”, consists in a floating platform which, through cables and winches, the seabed cleaning robot is attached. The structure is equipped with a set of sensors for underwater perception to control the robot and detect & identify the marine litter to be removed. Moreover, the robotic platform is characterized by two different tools that allow to collect the ML on the seabed: a drudge to suck up smaller litter and a gripper to grasps larger items like tires, parts of boats, fishing nets etc." assertion.