transformers go brum brum
Hi guys! Today we are going to implement Training data-efficient image transformers & distillation through attention a new method to perform knowledge distillation on Vision Transformers called DeiT.
You will soon see how elegant and simple this new approach is.
Code is here, an interactive version…
Hi guys, happy new year! Today we are going to implement the famous Vi(sion) T(ransformer) proposed in AN IMAGE IS WORTH 16X16 WORDS: TRANSFORMERS FOR IMAGE RECOGNITION AT SCALE.
Code is here, an interactive version of this article can be downloaded from here.
An interactive version of this article can be found here
DropBlock is available on glasses in my computer vision library!
Today we are going to use deep learning to create a face unlock algorithm. To complete our puzzle, we need three main pieces.
All the code used in this article is here
Recently, PyTorch has introduced its new production framework to properly serve models, called
torchserve.So, without further due, let’s present today’s roadmap:
To showcase torchserve, we will serve a fully…
Today we are going to build a semantic browser using deep learning to search in more than 50k papers about the recent COVID-19 disease.
The key idea is to encode each paper in…
The template is here
In this article, we present you a deep learning template based on Pytorch. This template aims to make it easier for you to start a new deep learning computer vision project with PyTorch. The main features are:
Today we are going to implement the famous ResNet from Kaiming He et al. (Microsoft Research) in Pytorch. It won the 1st place on the ILSVRC 2015 classification task.
ResNet and all its variants have been implemented in my library glasses
Code is here, an interactive version of this article…
There is one famous urban legend about computer vision. Around the 80s, the US military wanted to use neural networks to automatically detect camouflaged enemy tanks. They took a number of pictures of trees without tanks and then pictures with the same trees with tanks behind them. The results were…