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CASE STUDY

• SDM1 : Montane woodcreper - Gecomputation
• SDM1 : Montane woodcreper - Model
• SDM2 : Varied Thrush - Model
• Manipulate GSIM files
• Data type in GTiff
• Temporal interpolation of landsat images
• Dynamic Time Warping
• Estimating nitrogen and phosphorus concentrations in streams and rivers
• Estimating nitrogen concentrations in streams and rivers using NN
• Autoencoder (AE), Variational Autoencoder (VAE) and Generative Adversarial Network (GAN)
• LSTM Network
• Estimation of tree height using GEDI dataset - Data explore
• Estimation of tree height using GEDI dataset - Support Vector Machine for Regression (SVR)
• Estimation of tree height using GEDI dataset - Random Forest prediction
• Estimation of tree height using GEDI dataset - Perceptron 1
• Estimation of tree height using GEDI dataset - Clean Data - Perceptron 2
• Estimation of tree height using GEDI dataset - Neural Network 1
• Neural Nets (pt.3), Interpretability and Convolutional Neural Networks
• Using Multi-layer Perceptron and Convolutional Neural Networks for Satellite image classification.
• The real data
• LSTM for Regression Using the Window Method
• LSTM for Regression with Time Steps
• LSTM with Memory Between Batches
• Stacked LSTMs with Memory Between Batches
• Adding Early Stopping
• Multivariate Time-series - Data