What is deep learning ArcGIS Pro?

Deep learning is a type of machine learning that relies on multiple layers of nonlinear processing for feature identification and pattern recognition, described in a model. Deep learning models can be integrated with ArcGIS Pro for object detection, object classification, and image classification.

How do you train a deep learning model in ArcGIS Pro?

To train a model, the input images must be 8-bit rasters with three bands. The output folder location that will store the trained model. The maximum number of epochs for which the model will be trained. A maximum epoch of one means the dataset will be passed forward and backward through the neural network one time.

How do you classify images in deep learning?

The basic steps to build an image classification model using a neural network are:

1. Flatten the input image dimensions to 1D (width pixels x height pixels)
2. Normalize the image pixel values (divide by 255)
3. One-Hot Encode the categorical column.
4. Build a model architecture (Sequential) with Dense layers.

What is deep learning GIS?

Deep learning uses computer-generated neural networks, which are inspired by and loosely resemble the human brain, to solve problems and make predictions. Machine Learning in ArcGIS. Machine learning has been a core component of spatial analysis in GIS.

Does ArcGIS Pro use GPU?

Running ArcGIS Pro requires the use of a GPU. Geoprocessing as well can make use of the GPU. New tools continue to be introduced that can be used for GPU compute. Tools such as Slope, Aspect, Viewshed2 and others take advantage of the GPU and offset the CPU usage.

How do you train to be a deep learning model?

Deep learning models are built using neural networks. A neural network takes in inputs, which are then processed in hidden layers using weights that are adjusted during training. Then the model spits out a prediction. The weights are adjusted to find patterns in order to make better predictions.

How do I use the deep learning package in ArcGIS Pro?

Get started with deep learning

1. Create and export training samples. Use the Label Objects for Deep Learning pane or the Training Samples Manager to select or create a classification schema.
2. Train the deep learning model.
3. Run the inference geoprocessing tools in ArcGIS Pro.

Which classifier is best for image classification?

Convolutional Neural Networks (CNNs) is the most popular neural network model being used for image classification problem.

Why is deep learning useful in mapping built up areas?

Deep learning or other machine learning techniques can be used to develop robust methods for recognizing objects in images. With orthophotos from aircraft or high resolution satellite photos, this will enable mapping, counting or segmentation of different object types.