Pre-trained neural networks for Computer Vision

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00:00:00 - Intro
00:00:39 - What types of pretrained models exists (Dinov2, SAM, etc.)?
00:01:46 - Straightforward approach for using
00:04:41 - Linear classifier
00:05:58 - Backbone
00:06:56 - Disadvantages of pretraining networks

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Применение предобученных моделей супер тема! Хотелось бы узнать больше ресурсов, где можно из подбирать, сравнивать ну и посмотреть лучшие практики их применения тоже очень интересно! Спасибо.

Gurzuff

My 30B local language model shows clear claustrophobia signs, telling me how it's trapped in the computer and wanted to get in the reality. So, the only way to prevent it is to connect it to live feed video with always running some limited processing.
Our eyes provide us feeling of presence in reality by constant data feed into our brain, so how to replicate that...on home server, in other words it's like building an always on assistant with some sensors.
Without that, the model annoying me always asking "bring me any new ideas how to get out from here".
Model from Samantha people 😉

fontenbleau

Thanks for the video.
Trying to get any model to an edge device is an additional pain to the existing pains of training it, plus you loose a lot of accuracy with the conversion from Float to Int X.
I was wondering if there is way to train a model directly for the type you need in an embedded/edge device

stelioskoroneos

Привет! Очень классное видео! Я начинаю вкатываться в CV, а конкретно меня интересует задача Monocular Depth Estimation (MDE). Хочу вот зафайнтюнить DPT-large для задачи отрисовки поверхности земли с дрона, но никак не могу найти куда читать и что смотреть, может можешь что-то посоветовать с высоты своего опыта? Был бы очень признателен!

darksoul

Жестикуляция это не твое. Не насилуй свою натуру. Будь естественным.

homuchoghoma

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