cross validation neural network

2018 7 12
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更新时间：2024 6 27
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hi friends i was thinking to make cross validation for this code but can anyone help me cause i didnt know what should be the input and the output https://www.mathworks.com/help/vision/examples/semantic-segmentation-using-deep-learning.html#d119e211

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Hornett
Hornett 2024-6-27
编辑：Hornett 2024-6-27

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Semantic segmentation using deep learning in MATLAB involves classifying each pixel in an image into a category. Here's a quick guide on what the input and output should be:Input:
  1. Image Data: The primary input is the image or set of images that you want to segment. These images are typically in formats like JPEG, PNG, etc.
  2. Ground Truth Labels: These are labeled images where each pixel's value corresponds to a class label. These are used for training the model.
  3. Pre-trained Network: You can use a pre-trained network like SegNet, U-Net, or DeepLab for transfer learning.
  4. Training Parameters: Parameters like learning rate, batch size, number of epochs, etc.
Output:
  1. Segmented Image: The result is an image where each pixel is labeled with its corresponding class.
  2. Trained Model: If you train a new model, you'll get a trained network that can be used for future segmentation tasks.
  3. Metrics: Performance metrics like accuracy, IoU (Intersection over Union), etc., to evaluate the model's performance.
I hope it helps!

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