Deep Learning Tutorial Series

Download code and watch video series to learn and implement deep learning techniques
18.7K descargas
Actualizado 5 Dec 2017

Ver licencia

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 (2024). Deep Learning Tutorial Series (https://www.mathworks.com/matlabcentral/fileexchange/62990-deep-learning-tutorial-series), MATLAB Central File Exchange. Recuperado .

Compatibilidad con la versión de MATLAB
Se creó con R2017a
Compatible con cualquier versión
Compatibilidad con las plataformas
Windows macOS Linux
Categorías
Más información sobre Recognition, Object Detection, and Semantic Segmentation en Help Center y MATLAB Answers.
Agradecimientos

Inspiración para: Training 3D CNN models

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Versión Publicado Notas de la versión
1.1.0.0

minor bug fix in third file, "Demo_FeatureExtraction.mlx" :
on line 1 & 2, variable 'net' changed to 'convnet'

1.0.0.0

+ Fixed typo in code.