Deep Learning Workflow in ArcGIS
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Questions and Answers

What does the term 'Epoch' refer to in deep learning?

  • A single pass through the entire training dataset (correct)
  • The dimensions of image chips used for training
  • The size of the training dataset
  • The number of training examples in one iteration

    • What is the function of the Backbone Model in deep learning?

  • To extract important features from input data (correct)
  • To determine the batch size
  • To measure the training time
  • To store the training dataset

    • Which parameter is typically NOT associated with setting up a deep learning model?

  • Epoch
  • Training Duration (correct)
  • Batch Size
  • Chip Size

    • What does 'Chip Size' refer to in the context of deep learning?

    <p>The dimensions of image chips used for training</p> Signup and view all the answers

    What does the term 'Batch Size' indicate in deep learning?

    <p>The number of training examples used in one iteration</p> Signup and view all the answers

    What is the first step in the Deep Learning Workflow when using pre-trained models?

    <p>Labeling data</p> Signup and view all the answers

    What is credited for eliminating the data preparation process in the Deep Learning Workflow?

    <p>Using pre-trained models</p> Signup and view all the answers

    How many image chips were generated from 100 training samples in the study of Mangrove Forest?

    <p>531 image chips</p> Signup and view all the answers

    Which parameter is NOT typically associated with evaluating a deep learning model?

    <p>Mobility</p> Signup and view all the answers

    What aspect of the model does the 'Backbone' refer to in deep learning?

    <p>The underlying neural network architecture</p> Signup and view all the answers

    In the context of deep learning for the Mangrove Forest, what does 'F1' measure?

    <p>The balance between precision and recall</p> Signup and view all the answers

    What type of model development was conducted specifically for the province of Marinduque?

    <p>A deep learning model for Mangrove Forest</p> Signup and view all the answers

    What is the significance of the 'model_metrics.html' file in relation to deep learning?

    <p>It provides performance evaluation of the model.</p> Signup and view all the answers

    Which trial produced the highest recall value?

    <p>Trial 2</p> Signup and view all the answers

    What is the F1 score for Trial 5?

    <p>0.87718</p> Signup and view all the answers

    Which trial has the lowest accuracy value?

    <p>Trial 1</p> Signup and view all the answers

    What was the area coverage of the generated shapefiles in Trial No. 4?

    <p>83% area coverage</p> Signup and view all the answers

    How many sampling points were misclassified in the stratified random sampling?

    <p>3 out of 100</p> Signup and view all the answers

    What classification method was used in the deep learning study for Trial No. 4?

    <p>ResNet-34</p> Signup and view all the answers

    What was a noted issue in the comparative analysis of the generated feature class?

    <p>Salt-and-pepper noise</p> Signup and view all the answers

    Which trial generated a smooth learning curve indicating a good fit?

    <p>Trial 4</p> Signup and view all the answers

    What is the main purpose of using Deep Learning in the process described?

    <p>To improve accuracy and efficiency in image classification</p> Signup and view all the answers

    Which software is associated with the conventional image classification process?

    <p>eCognition Software</p> Signup and view all the answers

    What backbone model was used in the best-performing Deep Learning process for mangrove forest classification?

    <p>ResNet-34</p> Signup and view all the answers

    How many epochs were used in training the best Deep Learning model?

    <p>100 epochs</p> Signup and view all the answers

    What metric indicates the accuracy of the model developed for the mangrove forest?

    <p>0.96</p> Signup and view all the answers

    What was the duration required for the Deep Learning process?

    <p>10 working days</p> Signup and view all the answers

    How does the Deep Learning process handle training and testing data?

    <p>80% for training and 20% for testing</p> Signup and view all the answers

    What is one drawback of the conventional image classification process compared to Deep Learning?

    <p>It takes longer to complete the data preparation phase.</p> Signup and view all the answers

    What are the independent variables in the deep learning model for the Mangrove Forest?

    <p>Model type and Training samples</p> Signup and view all the answers

    Which ResNet architecture has a higher validation percent according to the sample data?

    <p>ResNet-50 with 100 training samples</p> Signup and view all the answers

    What type of learning is indicated by a learning curve that starts high and decreases over time?

    <p>Overfit Learning</p> Signup and view all the answers

    If a model is underfitting, what characteristic would you expect to see in the learning curves?

    <p>Lower validation performance throughout</p> Signup and view all the answers

    What is the dependent variable in the deep learning model being developed?

    <p>Backbone model</p> Signup and view all the answers

    Which statement best describes a valid characteristic of good fit learning curves?

    <p>They exhibit high performance on both training and validation.</p> Signup and view all the answers

    Which trial number retains the highest validation percent from the given data?

    <p>Trial 2</p> Signup and view all the answers

    What does the x-axis represent in a learning curve?

    <p>Progress</p> Signup and view all the answers

    Study Notes

    Deep Learning Workflow

    • The workflow consists of 4 steps: prepare sentinel-۲ image, prepare training data, train a model, and classify pixels
    • Training data is prepared using a training sample manager by manually digitized training samples
    • Training data is exported after parameters such as epoch, batch size, chip size, and metadata format are set
    • An epoch is a single pass through the entire training dataset
    • Batch size refers to the number of training examples used in one iteration of the training process
    • Chip size refers to the dimensions of image chips used for training models
    • Backbone model is like a central processing unit that extracts important features from input data

    Deep Learning Workflow in ArcGIS

    • There are two options for deep learning in ArcGIS:
      • Use pre-trained models
      • Train your own model
    • Training your own model requires labelling data
    • For pre-trained AI models, this step is eliminated
    • The training model folder contains:
      • ModelCharacteristics
      • model_metrics.html
      • Model...dlpk
      • Model...emd
      • Model...pth

    Mangrove Forest Training Libraries

    • 100 training samples generated 531 image chips

    Mangrove Forest Deep Learning Model

    • Model parameters include:
      • training type
      • batch size
      • validation percentage
      • chip size
      • backbone model
    • Evaluation metrics include:
      • precision
      • recall
      • F1 score
      • accuracy
    • ResNet 34 and 50 are the most effective models
    • Independent variables are: training samples, model type, and chip size
    • Dependent variables are : validation percent, backbone model, and epoch

    Learning Curves

    • Three common dynamics of learning curves are:
      • Underfit learning
      • Overfit learning
      • Good fit learning
    • The X axis represents progress
    • The Y axis represents performance

    Mangrove Forest Model Evaluation

    • Model #4 is the best model as it generated a smooth learning curve
    • There are five trials

    Comparative Analysis of the Mangrove Forest

    • The analysis compared:
      • 2024 Deep Learning Study with 2020 Land Cover Map
    • Parameters for comparison:
      • Fitness of the generated feature class
      • Area of the generated shapefiles
      • Stratified Random Sampling Points and misclassifications of non-mangrove areas
    • Sites are located in the municipalities of Mogpog, Santa Cruz, Boac & Torrijos
    • “Salt and pepper” misclassifications were found

    Comparison of Conventional and Deep Learning Processes

    • Deep learning takes about 5 working days
    • Conventional processes take 10 working days
    • Deep learning required 1-2 hours to train the model
    • Conventional processes require specialized software like eCognition Software and ArcMap

    Mangrove Forest Conclusions

    • The best model developed for the mangrove forest used U-net with ResNet-34, 32 batch size and 100 epochs
    • The model generated 0.96 accuracy
    • A strong correlation was observed in the learning curve using 20% of data for testing and 80% for training.

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    AI_my Slides.pptx

    Description

    This quiz covers the essential steps in the deep learning workflow specific to ArcGIS, detailing processes such as preparing images, training data, and model training. Learn the importance of components like epochs, batch size, and chip size, and discover how to utilize pre-trained models or train your own. Test your knowledge on this vital aspect of geospatial data analysis.

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