Update items_metadata.yaml

updated items_metadata

Author: mohi9282

items_metadata.yaml

@@ -879,6 +879,42 @@ samples:
 #   licenseInfo: ""
 #   runtime: advanced
 #   tags: ["Data Science", "GIS", "Site Suitability", "Raster Analysis"]
+# - title: Detecting Mussel Farms using Deep Learning
+#   url: https://www.arcgis.com/home/item.html?id=ff6e52bfa7714fe89c1345fd3fa9b7c0
+#   path: ./samples/04_gis_analysts_data_scientists/detecting_mussel_farms_using_deep_learning.ipynb
+#   thumbnail: ./static/thumbnails/default.png
+#   snippet: In this notebook, we will train a deep learning model to detect mussel farms in high-resolution imagery of the Ria De Arousa region of Spain.
+#   description: In this notebook, we will train a deep learning model to detect mussel farms in high-resolution imagery of the Ria De Arousa region of Spain.
+#   licenseInfo: ""
+#   runtime: advanced
+#   tags: ["Data Science", "GIS", "Site Suitability", "Raster Analysis"]
+# - title: Forecasting Air Temperature in California using ResCNN model
+#   url: https://www.arcgis.com/home/item.html?id=ecefff2763404106b87c02ef70123930
+#   path: ./samples/04_gis_analysts_data_scientists/forecasting_air_temperature_in_california_using_rescnn_model.ipynb
+#   thumbnail: ./static/thumbnails/default.png
+#   snippet: In this study, the deep learning TimeSeriesModel from arcgis.learn is used to predict monthly air temperature for two years.
+#   description: In this study, the deep learning TimeSeriesModel from arcgis.learn is used to predict monthly air temperature for two years.
+#   licenseInfo: ""
+#   runtime: advanced
+#   tags: ["Data Science", "GIS", "Site Suitability", "Raster Analysis"]
+# - title: Count cars in aerial imagery using deep learning
+#   url: https://www.arcgis.com/home/item.html?id=b80e02d207aa43a193601afe2390bf86
+#   path: ./samples/04_gis_analysts_data_scientists/count_cars_in_aerial_imagery_using_deep_learning.ipynb
+#   thumbnail: ./static/thumbnails/default.png
+#   snippet: The pre-trained Car Detection-USA model is used to detect cars in high-resolution drone or aerial imagery.
+#   description: The pre-trained Car Detection-USA model is used to detect cars in high-resolution drone or aerial imagery.
+#   licenseInfo: ""
+#   runtime: advanced
+#   tags: ["Data Science", "GIS", "Site Suitability", "Raster Analysis"]
+# - title: Classify land cover to measure shrinking lakes
+#   url: https://www.arcgis.com/home/item.html?id=32f8860e155d4f03987b94be876d73c1
+#   path: ./samples/04_gis_analysts_data_scientists/measure_shrinking_lakes_using_deep_learning.ipynb
+#   thumbnail: ./static/thumbnails/default.png
+#   snippet: This sample aims to demonstrate how ArcGIS pre-trained models can be used to generate landcover from imageries of different time periods.
+#   description: This sample aims to demonstrate how ArcGIS pre-trained models can be used to generate landcover from imageries of different time periods.
+#   licenseInfo: ""
+#   runtime: advanced
+#   tags: ["Data Science", "GIS", "Site Suitability", "Raster Analysis"]
 
 guides: []
 labs: