thtang/DLCV2018SPRING

Deep Learning for Computer Vision (CommE 5052) in NTU

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Emerging

This resource provides practical examples and code for applying deep learning techniques to various computer vision challenges. It demonstrates how to process images for tasks like classifying objects, segmenting different parts of an image, or even generating new images. This is ideal for students, researchers, or practitioners in computer vision looking to understand or implement core deep learning concepts.

No commits in the last 6 months.

Use this if you are studying or working with computer vision and need hands-on examples for deep learning algorithms, from basic image analysis to advanced generation and recognition tasks.

Not ideal if you are looking for a plug-and-play solution for a specific application without delving into the underlying code and algorithms.

computer-vision-education image-analysis machine-learning-research semantic-segmentation action-recognition
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 18 / 25

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Stars

43

Forks

12

Language

Jupyter Notebook

License

Apache-2.0

Last pushed

Mar 24, 2023

Commits (30d)

0

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