Discover hangyao/Udacity_SDCND_traffic-signs Open Source project

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Jupyter Notebook
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MIT License
Created almost 8 years ago
Updated almost 8 years ago

hangyao

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Built and trained a deep neural network to classify traffic signs, using TensorFlow. Experimented with different network architectures. Performed image pre-processing and validation to guard against overfitting.

street_view_house_numbers

Explored CNNs with TensorFlow to create models for cropped single-digit and original multi-digit images from SVHN dataset.

Jupyter Notebook

Udacity_SDCND_Vehicle-Detection

Created a vehicle detection and tracking pipeline with OpenCV, histogram of oriented gradients (HOG), and support vector machines (SVM). Optimized and evaluated the model on video data from a automotive camera taken during highway driving.

Jupyter Notebook

Java-Programming-ITSE-2317

Java

Udacity_SDCND_behavioral-cloning

Built and trained a convolutional neural network for end-to-end driving in a simulator, using TensorFlow and Keras. Used optimization techniques such as regularization and dropout to generalize the network for driving on multiple tracks.

Python

hangyao/Udacity_SDCND_traffic-signs

hangyao

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