Method of applying remote sensing image to large model

The methods of applying remote sensing images to large models include data collection and preparation, feature extraction and selection, data set construction, model selection and training, result interpretation and application.

1. data acquisition and preparation: obtain high-resolution remote sensing image data from appropriate data providers, satellites or aviation platforms. Pre-processing the obtained remote sensing image, including correction, radiation correction, geometric correction, atmospheric correction, etc. To ensure the image quality and consistency.

2. Feature extraction and selection: To extract useful features from remote sensing images, computer vision and image processing technologies can be used, such as convolutional neural network (CNN) and feature detection algorithm.

3. Data set construction: according to the needs of the task, the remote sensing images are marked and labeled, such as target detection, classification, segmentation and so on. The labeled remote sensing image data set is divided into training set, verification set and test set, which are used for model training, optimization and evaluation.

4. Model selection and training: choose a large model architecture suitable for the task, such as deep learning models (such as convolutional neural networks, circular neural networks, etc.). ) or other machine learning models. Use the training set to train the selected model, and adjust the hyperparameter and optimize the model as needed.

5. Model evaluation and verification: use the verification set to evaluate the performance and accuracy of the model, and improve and adjust the model as needed. The test set is used to verify the final model and evaluate its performance and generalization ability on real data.

6. Interpretation and application of results: Explain and analyze the output of the model, and understand the contribution of the prediction results and characteristics of the model to the task. The model is applied to practical scenes, such as remote sensing image classification, target detection, ground object recognition and so on.

Remote sensing image is the image data of the earth's surface obtained by remote sensing technology. Remote sensing technology uses sensors and equipment to obtain information from distant places, such as airplanes, satellites or other remote sensing platforms.