priyanka_review_update

Author: sdash77

samples/04_gis_analysts_data_scientists/cloud_removal_using_pre-trained_deep_learning_model_and_raster_function.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# cloud removal using pre-trained deep learning model and raster function\n",
+    "# cloud removal using pretrained deep learning model and raster function\n",
     "\n",
     "> * 🔬 Data Science\n",
     "> * 🥠 Deep Learning and image translation"
@@ -20,7 +20,7 @@
     "* [Necessary imports](#Necessary-imports)\n",
     "* [Connect to your GIS](#Connect-to-your-GIS)\n",
     "* [Generate cloud mask](#Generate-cloud-mask)\n",
-    "  * [Use cloud mask generation pre-trained model](#Use-cloud-mask-generation-pre-trained-model)\n",
+    "  * [Use cloud mask generation pretrained model](#Use-cloud-mask-generation-pretrained-model)\n",
     "  * [Reclassify cloud types in cloud mask](#Reclassify-cloud-types-in-cloud-mask)\n",
     "    * [Visualize the generated cloud mask](#Visualize-the-generated-cloud-mask)\n",
     "* [Use stepwise local radiometric adjustment raster function](#Use-stepwise-local-radiometric-adjustment-raster-function)\n",
@@ -41,7 +41,7 @@
    "source": [
     "The goal of this notebook, is to detect and replace the cloud contaminated region of the satellite images. Clouds often create obstructions in satellite imagery that can hinder results in processes like land cover classification and time series analysis. In a general perspective, it can be seen as a image denoising problem, in which clouds are considered as noise in respect to land surface in images. \n",
     "\n",
-    "In this notebook, we will detect and replace cloud contaminated regions of satellite imagery by combining a pre-trained deep learning model, available in living atlas, and an image processing technique, available in [raster functions](https://github.com/Esri/raster-functions)."
+    "In this notebook, we will detect and replace cloud contaminated regions of satellite imagery by combining a pretrained deep learning model, available in living atlas, and an image processing technique, available in [raster functions](https://github.com/Esri/raster-functions)."
    ]
   },
   {
@@ -185,14 +185,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Use the pre-trained cloud mask generation model"
+    "### Use the pretrained cloud mask generation model"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The pre-trained cloud mask generation model has been trained on sentinel-L2A imagery and is used to generate a cloud mask for an input raster. The cloud mask will be used by a Stepwise local radiometric adjustment (SLRA) raster function as guidance for removing cloud contaminated pixels from the target raster."
+    "The pretrained cloud mask generation model has been trained on sentinel-L2A imagery and is used to generate a cloud mask for an input raster. The cloud mask will be used by a Stepwise local radiometric adjustment (SLRA) raster function as guidance for removing cloud contaminated pixels from the target raster."
    ]
   },
   {
@@ -244,7 +244,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The pre-trained cloud mask model will classify clouds into 3 classes. low, medium, and high density. As we want to remove all cloud contaminated regions, we will reclassify these 3 classes into one single class."
+    "The pretrained cloud mask model will classify clouds into 3 classes. low, medium, and high density. As we want to remove all cloud contaminated regions, we will reclassify these 3 classes into one single class."
    ]
   },
   {
@@ -369,7 +369,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "In this notebook, we have demonstrated a method to remove clouds from satellite imagery with a combination of a pre-trained deep learning model and Esri raster functions. Further, it demonstrated how you can use your developed python raster functions in ArcGIS Pro."
+    "In this notebook, we have demonstrated a method to remove clouds from satellite imagery with a combination of a pretrained deep learning model and Esri raster functions. Further, it demonstrated how you can use your developed python raster functions in ArcGIS Pro."
    ]
   },
   {
@@ -389,7 +389,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -403,7 +403,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.11"
+   "version": "3.9.15"
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