Hi JIBIN,
To create a network architecture for predicting the length and width of an image using MATLAB, you can follow these steps:
- Data Preparation: Collect a dataset of images along with their corresponding length and width values. Split the dataset into training and testing sets. Whatever ratio you can use to split out the dataset into training and testing.
- Preprocessing: Resize all the images to a fixed size, convert them to grayscale if necessary, and normalize the pixel values to a suitable range (e.g., [0, 1]).
- Network Architecture: Define the architecture of your neural network. You can use MATLAB's Deep Learning Toolbox to create the network.
- Training Options: Set the training options for your network. Specify the optimizer, learning rate, mini-batch size, and the number of epochs.
- Training: Train your network using the prepared dataset and training options. Use the trainNetwork function in MATLAB.
- Evaluation: Evaluate the performance of your trained network on the testing dataset using the predict function. Calculate appropriate metrics such as mean squared error (MSE) or mean absolute error (MAE) to assess the accuracy of your predictions.
To understand the usage of deep learning toolbox in MATLAB in detail, you can follow this documentation link: https://in.mathworks.com/help/deeplearning/examples.html?s_tid=CRUX_topnav
Remember to adjust the network architecture, training options, and evaluation metrics based on your specific problem and dataset.
