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Nota del editor: This file was selected as MATLAB Central Pick of the Week
The code provides hands-on examples to implement convolutional neural networks (CNNs) for object recognition. The three demos have associated instructional videos that will allow for a complete tutorial experience to understand and implement deep learning techniques.
The demos include:
- Training a neural network from scratch
- Using a pre-trained model (transfer learning)
- Using a neural network as a feature extractor
The corresponding videos for the demos are located here: https://www.mathworks.com/videos/series/deep-learning-with-MATLAB.html
The use of a GPU and Parallel Computing Toolbox™ is recommended when running the examples. Demo 3 requires Statistics and Machine Learning Toolbox™ in addition to the required products below.
Citar como
MathWorks Deep Learning Toolbox Team (2026). Deep Learning Tutorial Series (https://la.mathworks.com/matlabcentral/fileexchange/62990-deep-learning-tutorial-series), MATLAB Central File Exchange. Recuperado .
Agradecimientos
Inspiración para: TFCNN-BiGRU, Training 3D CNN models
Categorías
Más información sobre Recognition, Object Detection, and Semantic Segmentation en Help Center y MATLAB Answers.
Información general
- Versión 1.1.0.0 (23,3 KB)
Compatibilidad con la versión de MATLAB
- Compatible con cualquier versión
Compatibilidad con las plataformas
- Windows
- macOS
- Linux
