Deep Learning Tutorial Series

Download code and watch video series to learn and implement deep learning techniques
Aktualisiert 5. Dez 2017

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Anmerkung des Herausgebers: 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:
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.

Zitieren als

MathWorks Deep Learning Toolbox Team (2024). Deep Learning Tutorial Series (, MATLAB Central File Exchange. Abgerufen .

Kompatibilität der MATLAB-Version
Erstellt mit R2017a
Kompatibel mit allen Versionen
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Mehr zu Recognition, Object Detection, and Semantic Segmentation finden Sie in Help Center und MATLAB Answers

Inspiriert: TFCNN-BiGRU, Training 3D CNN models

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Version Veröffentlicht Versionshinweise

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

+ Fixed typo in code.