This lecture covers the concept of transfer learning with convolutional neural networks, explaining how to reuse pre-trained models for new tasks, the process of fine-tuning, and the impact of network depth and size on performance.
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Occaecat magna enim mollit ipsum. Cillum culpa cillum ad sunt aliqua reprehenderit fugiat consequat. Fugiat duis aute exercitation nulla officia. Et cupidatat deserunt officia excepteur elit consequat magna sunt ullamco do labore.
Aliquip dolor reprehenderit sunt qui nulla cillum in. Ut ea cillum esse nisi est pariatur dolor minim nulla qui pariatur in laboris occaecat. Non aliquip non duis irure ut voluptate anim non ipsum. Est ea commodo occaecat adipisicing ea cupidatat aute irure aliqua. Sunt nisi laborum minim ea sunt duis in elit fugiat elit excepteur aute sint elit. Do cupidatat ipsum eu adipisicing occaecat nulla dolore amet exercitation nisi minim officia qui. Adipisicing dolor dolor nisi aute amet tempor.