QGIS Python Plugins Repository
Plugins tagged with: deep-learning
9 records found —
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| Name | Featured | Downloads | Author | Latest Plugin Version | Created on | Stars (votes) | Stable | Exp. | |
|---|---|---|---|---|---|---|---|---|---|
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Artificial Intelligence Forecasting Remote Sensing | — | 6808 | Hafssa Naciri; Nizar Ben Achhab; Fatima Ezahrae Ezzaher; Naoufal Raissouni | 2024-01-22T13:46:56.727690+00:00 | 2023-10-24T13:34:55.559166+00:00 | (16) |
0.3 | — |
| This plugin allows time series forecasting using deep learning models. | |||||||||
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buildSeg | — | 6561 | deepbands (Yizhou Chen and Youssef Harby) | 2022-06-05T07:14:59.472605+00:00 | 2021-12-14T13:24:49.738082+00:00 | (6) |
0.3 | 0.1 |
| Deep learning building segmentation. | |||||||||
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Deep Learning Datasets Maker | — | 3827 | deepbands (Youssef Harby and Yizhou Chen) | 2022-01-19T02:15:29.531264+00:00 | 2021-12-11T04:40:00.358152+00:00 | (9) |
— | 0.2.1 |
| tools to handle raster and vector data to split it into small pieces equaled in size for machine learning datasets | |||||||||
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DeepLearningTools | — | 3484 | Brazilian Army Geographic Service | 2021-03-08T23:11:31.032708+00:00 | 2020-10-27T17:29:01.393424+00:00 | (1) |
— | 0.2.0 |
| QGIS plugin to aid training Deep Learning Models | |||||||||
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Deepness: Deep Neural Remote Sensing | — | 27872 | PUT Vision | 2024-10-04T09:42:41.086754+00:00 | 2022-10-20T11:38:13.982136+00:00 | (92) |
0.6.4 | 0.3.0 |
| Inference of deep neural network models (ONNX) for segmentation, detection and regression | |||||||||
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Mapflow | — | 116171 | Geoalert | 2024-11-06T10:18:14.069612+00:00 | 2021-07-09T15:15:42.595345+00:00 | (99) |
2.6.3 | — |
| Extract real-world objects from satellite imagery with Mapflow by Geoalert. Mapflow provides AI mapping pipelines for building footprints, roads, fields, forest and construction sites. | |||||||||
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Nimbo's Earth Basemaps | — | 13346 | Kermap | 2024-07-09T10:07:28.144639+00:00 | 2023-09-04T14:12:30.873471+00:00 | (145) |
0.7 | — |
| Nimbo's Earth Basemaps is an innovative Earth observation service providing cloud-free, homogenous mosaics of the world's entire landmass as captured by satellite imagery. Updated every month.<br><br>Along with this unprecedented refresh rate, Nimbo Earth Basemaps provides users with 4 data layers every month :<br><br>- Natural colors (RGB)<br>- Infrared (NIR)<br>- NDVI (vegetation helath index)<br>- Radar (SAR, VV/VH combination)<br><br>Maximum image resolution is 10m/px.<br>Images are served in WMS/WMTS format.<br><br>Nimbo Earth Basemaps meets a variety of requirements for geospatial analysis professionals, including visualizations fit for machine learning algorithm implementation, monitoring tasks and training models based on time series.<br><br>Nimbo Earth Basemaps' views consist of monthly syntheses using imagery from Sentinel 1 and 2 satellites from the European Copernicus programme.<br><br>Nimbo is developed and published exclusively by Kermap:<br><a href="https://kermap.com" >https://kermap.com</a> | |||||||||
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Produce Training Data For Deep Learning | — | 5418 | Pratyush Tripathy | 2020-01-30T06:51:17.890827+00:00 | 2020-01-10T07:14:47.578509+00:00 | (61) |
— | 0.4 |
| The plugin fragments the remote sensing image, to be used as deep learning training datasets. | |||||||||
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TreeEyed | — | 1472 | Andrés Felipe Ruiz-Hurtado, Tropical Forages - CIAT | 2024-09-05T22:07:13.241867+00:00 | 2024-09-05T22:07:11.437526+00:00 | (18) |
0.1 | — |
| TreeEyed is a QGIS plugin for tree monitoring using AI. | |||||||||
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