derektan95/deeplearning-for-computervision-eecs598
This course is a deep dive into details of neural-network based deep learning methods for computer vision. It is offered by the University of Michigan, Ann Arbor (EECS 598).
This project provides practical exercises for understanding deep learning methods specifically applied to computer vision tasks. It takes image datasets, such as CIFAR-10, and processes them through various neural network architectures to produce classifications or other visual interpretations. The materials are ideal for students or practitioners looking to learn how these advanced techniques work by hands-on experimentation.
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Use this if you are a student or researcher wanting to learn and practice deep learning for computer vision using pre-configured exercises.
Not ideal if you are looking for a plug-and-play tool for immediate application of deep learning models without an interest in the underlying mechanisms or code.
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Jun 01, 2021
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