BrRacemeCounter: Mask R-CNN for Raceme Instance Segmentation
This is an adapted implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bounding boxes and segmentation masks for each instance of an object in the image. It's based on Feature Pyramid Network (FPN) and a ResNet50 or ResNet101 backbone. This project detects and count...
| Main Authors: | , , |
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| Format: | Software |
| Language: | Inglés |
| Published: |
2024
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| Online Access: | https://hdl.handle.net/10568/168316 |
| _version_ | 1855535328745488384 |
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| author | International Center for Tropical Agriculture (CIAT) Tropical Forages Program Arrechea-Castillo, Darwin Alexis Cardoso Arango, Juan Andres |
| author_browse | Arrechea-Castillo, Darwin Alexis Cardoso Arango, Juan Andres International Center for Tropical Agriculture (CIAT) Tropical Forages Program |
| author_facet | International Center for Tropical Agriculture (CIAT) Tropical Forages Program Arrechea-Castillo, Darwin Alexis Cardoso Arango, Juan Andres |
| author_sort | International Center for Tropical Agriculture (CIAT) Tropical Forages Program |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | This is an adapted implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bounding boxes and segmentation masks for each instance of an object in the image. It's based on Feature Pyramid Network (FPN) and a ResNet50 or ResNet101 backbone.
This project detects and count the total amount of racemes in tropical forages (Urochloa spp.) throught an web or a desktop based application |
| format | Software |
| id | CGSpace168316 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| record_format | dspace |
| spelling | CGSpace1683162025-03-19T13:37:16Z BrRacemeCounter: Mask R-CNN for Raceme Instance Segmentation International Center for Tropical Agriculture (CIAT) Tropical Forages Program Arrechea-Castillo, Darwin Alexis Cardoso Arango, Juan Andres machine learning imagery-computer vision racemes This is an adapted implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bounding boxes and segmentation masks for each instance of an object in the image. It's based on Feature Pyramid Network (FPN) and a ResNet50 or ResNet101 backbone. This project detects and count the total amount of racemes in tropical forages (Urochloa spp.) throught an web or a desktop based application 2024-12-19 2024-12-24T05:15:27Z 2024-12-24T05:15:27Z Software https://hdl.handle.net/10568/168316 en Open Access International Center for Tropical Agriculture (CIAT) Tropical Forages Program; Arrechea-Castillo, D.A.; Cardoso Arango, J.A. (2024) BrRacemeCounter: Mask R-CNN for Raceme Instance Segmentation. |
| spellingShingle | machine learning imagery-computer vision racemes International Center for Tropical Agriculture (CIAT) Tropical Forages Program Arrechea-Castillo, Darwin Alexis Cardoso Arango, Juan Andres BrRacemeCounter: Mask R-CNN for Raceme Instance Segmentation |
| title | BrRacemeCounter: Mask R-CNN for Raceme Instance Segmentation |
| title_full | BrRacemeCounter: Mask R-CNN for Raceme Instance Segmentation |
| title_fullStr | BrRacemeCounter: Mask R-CNN for Raceme Instance Segmentation |
| title_full_unstemmed | BrRacemeCounter: Mask R-CNN for Raceme Instance Segmentation |
| title_short | BrRacemeCounter: Mask R-CNN for Raceme Instance Segmentation |
| title_sort | brracemecounter mask r cnn for raceme instance segmentation |
| topic | machine learning imagery-computer vision racemes |
| url | https://hdl.handle.net/10568/168316 |
| work_keys_str_mv | AT internationalcenterfortropicalagricultureciattropicalforagesprogram brracemecountermaskrcnnforracemeinstancesegmentation AT arrecheacastillodarwinalexis brracemecountermaskrcnnforracemeinstancesegmentation AT cardosoarangojuanandres brracemecountermaskrcnnforracemeinstancesegmentation |