Deep Learning Tutorial Series
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: 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.
Zitieren als
MathWorks Deep Learning Toolbox Team (2026). Deep Learning Tutorial Series (https://de.mathworks.com/matlabcentral/fileexchange/62990-deep-learning-tutorial-series), MATLAB Central File Exchange. Abgerufen.
Kompatibilität der MATLAB-Version
Plattform-Kompatibilität
Windows macOS LinuxKategorien
- Image Processing and Computer Vision > Computer Vision Toolbox > Recognition, Object Detection, and Semantic Segmentation >
Tags
Quellenangaben
Inspiriert: TFCNN-BiGRU, Training 3D CNN models
Live Editor erkunden
Erstellen Sie Skripte mit Code, Ausgabe und formatiertem Text in einem einzigen ausführbaren Dokument.
DeepLearningDemos/
DeepLearningDemos/
| Version | Veröffentlicht | Versionshinweise | |
|---|---|---|---|
| 1.1.0.0 | minor bug fix in third file, "Demo_FeatureExtraction.mlx" :
|
||
| 1.0.0.0 | + Fixed typo in code. |
