Podcast
Questions and Answers
What does the term 'Epoch' refer to in deep learning?
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?
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?
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?
What does 'Chip Size' refer to in the context of deep learning?
What does the term 'Batch Size' indicate in deep learning?
What does the term 'Batch Size' indicate in deep learning?
What is the first step in the Deep Learning Workflow when using pre-trained models?
What is the first step in the Deep Learning Workflow when using pre-trained models?
What is credited for eliminating the data preparation process in the Deep Learning Workflow?
What is credited for eliminating the data preparation process in the Deep Learning Workflow?
How many image chips were generated from 100 training samples in the study of Mangrove Forest?
How many image chips were generated from 100 training samples in the study of Mangrove Forest?
Which parameter is NOT typically associated with evaluating a deep learning model?
Which parameter is NOT typically associated with evaluating a deep learning model?
What aspect of the model does the 'Backbone' refer to in deep learning?
What aspect of the model does the 'Backbone' refer to in deep learning?
In the context of deep learning for the Mangrove Forest, what does 'F1' measure?
In the context of deep learning for the Mangrove Forest, what does 'F1' measure?
What type of model development was conducted specifically for the province of Marinduque?
What type of model development was conducted specifically for the province of Marinduque?
What is the significance of the 'model_metrics.html' file in relation to deep learning?
What is the significance of the 'model_metrics.html' file in relation to deep learning?
Which trial produced the highest recall value?
Which trial produced the highest recall value?
What is the F1 score for Trial 5?
What is the F1 score for Trial 5?
Which trial has the lowest accuracy value?
Which trial has the lowest accuracy value?
What was the area coverage of the generated shapefiles in Trial No. 4?
What was the area coverage of the generated shapefiles in Trial No. 4?
How many sampling points were misclassified in the stratified random sampling?
How many sampling points were misclassified in the stratified random sampling?
What classification method was used in the deep learning study for Trial No. 4?
What classification method was used in the deep learning study for Trial No. 4?
What was a noted issue in the comparative analysis of the generated feature class?
What was a noted issue in the comparative analysis of the generated feature class?
Which trial generated a smooth learning curve indicating a good fit?
Which trial generated a smooth learning curve indicating a good fit?
What is the main purpose of using Deep Learning in the process described?
What is the main purpose of using Deep Learning in the process described?
Which software is associated with the conventional image classification process?
Which software is associated with the conventional image classification process?
What backbone model was used in the best-performing Deep Learning process for mangrove forest classification?
What backbone model was used in the best-performing Deep Learning process for mangrove forest classification?
How many epochs were used in training the best Deep Learning model?
How many epochs were used in training the best Deep Learning model?
What metric indicates the accuracy of the model developed for the mangrove forest?
What metric indicates the accuracy of the model developed for the mangrove forest?
What was the duration required for the Deep Learning process?
What was the duration required for the Deep Learning process?
How does the Deep Learning process handle training and testing data?
How does the Deep Learning process handle training and testing data?
What is one drawback of the conventional image classification process compared to Deep Learning?
What is one drawback of the conventional image classification process compared to Deep Learning?
What are the independent variables in the deep learning model for the Mangrove Forest?
What are the independent variables in the deep learning model for the Mangrove Forest?
Which ResNet architecture has a higher validation percent according to the sample data?
Which ResNet architecture has a higher validation percent according to the sample data?
What type of learning is indicated by a learning curve that starts high and decreases over time?
What type of learning is indicated by a learning curve that starts high and decreases over time?
If a model is underfitting, what characteristic would you expect to see in the learning curves?
If a model is underfitting, what characteristic would you expect to see in the learning curves?
What is the dependent variable in the deep learning model being developed?
What is the dependent variable in the deep learning model being developed?
Which statement best describes a valid characteristic of good fit learning curves?
Which statement best describes a valid characteristic of good fit learning curves?
Which trial number retains the highest validation percent from the given data?
Which trial number retains the highest validation percent from the given data?
What does the x-axis represent in a learning curve?
What does the x-axis represent in a learning curve?
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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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.
