thtang/DLCV2018SPRING
Deep Learning for Computer Vision (CommE 5052) in NTU
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.
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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.
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Jupyter Notebook
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Apache-2.0
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Last pushed
Mar 24, 2023
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