Saturday, April 17, 2021
  • Setup menu at Appearance » Menus and assign menu to Top Bar Navigation
Advertisement
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
No Result
View All Result
Home Neural Networks

Vision Transformers — attention for vision task. | by nachiket tanksale | Nov, 2020

November 10, 2020
in Neural Networks
Vision Transformers — attention for vision task. | by nachiket tanksale | Nov, 2020
586
SHARES
3.3k
VIEWS
Share on FacebookShare on Twitter

Recently there’s paper “An Image is Worth 16×16 Words: Transformers for Image Recognition at Scale” on open-review. It uses pretrained transformers at scale for vision tasks. Transformers are highly successful for language tasks, but haven’t seen that much success for vision. In vision, transformers are either applied in conjunction with Convolutional Neural Networks(CNN) or to replace some components of CNN. Recently transformers has shown good results on object detection (End-to-End Object Detection with Transformers). This paper applies transformers to vision task without using CNN and shows that state-of-art results can be obtained without CNN.

The Cost of attention is quadratic. So for images, every pixel needs to attend to every other pixel which is costly. There are different methods used to overcome this like local attention (attend to subset of input) or global attention. This paper uses global attention.

You might also like

AI and Human Rights, A Story About Equality | by bundleIQ | Mar, 2021

The “Blue Brain” Project-A mission to build a simulated Brain | by The A.I. Thing | Mar, 2021

Templates Vs Machine Learning OCR | by Infrrd | Mar, 2021

Model Architecture

The architecture follows very closely the transformers. This is done to use transformer architecture that has scaled well for NLP tasks and optimised implementation of the architecture can be used out of box from different libraries. The difference came from how images are fed as sequence of patches to transformers.

Patch Embedding

Transformer receives 1D embedding as input. To handle 2D image input., the image is divided into sequence of flattened 2D fix size image patches. So , image of size H*W*C is divided into sequence of patches of size N*(P2*C), where P*P is size of patch.

1. How to automatically deskew (straighten) a text image using OpenCV

2. Explanation of YOLO V4 a one stage detector

3. 5 Best Artificial Intelligence Online Courses for Beginners in 2020

4. A Non Mathematical guide to the mathematics behind Machine Learning

Before passing the patches to transformer , Paper suggest them to put them through linear projection to get patch embedding. The official jax implementation uses conv layer for the same.(can be done by simple linear layer but its costly). Below is snippet of code from my pytorch implementation for the same.

As with BERT’s [class] token, learnable class token is concatenated to patch embedding, which serves as class representation.

To retain positional information of patches, positional embedding are added to patch embedding. Paper have explored 2D-aware variant as well as standard 1D embedding for position , but haven’t seen much advantage of one over the other.

Hybrid Architecture.

Alternative can be to use intermediate feature maps of a ResNet instead of image patches as input to transformers. The 2D feature map from earlier layers of resnet are flattened and projected to transformer dimension and fed to transformer. class token and positional embedding are added as mentioned.

Artificial Intelligence Jobs

Vision transformer is pretrained on large datasets like Imagenet-1k, Imagenet-21k, JFT-300M. And based on task, it’s fine tuned on the task dataset. The table below shows the results of fine-tuning on vision transformer pretrained on JFT-300M.

You can find my repo for pytorch implementation here. I have used Imagenet-1k pretrained weights from https://github.com/rwightman/pytorch-image-models/ and updated checkpoint for my implementation. The checkpoint can be found here.

You can also find pytorch Kaggle Kernel for fine tuning vision transformer on tpu here.

Credit: BecomingHuman By: nachiket tanksale

Previous Post

Tech giants not convinced Australia's critical infrastructure Bill is currently fit for purpose

Next Post

Google Photos 5.18 lets you improve app's machine learning

Related Posts

AI and Human Rights, A Story About Equality | by bundleIQ | Mar, 2021
Neural Networks

AI and Human Rights, A Story About Equality | by bundleIQ | Mar, 2021

April 17, 2021
The “Blue Brain” Project-A mission to build a simulated Brain | by The A.I. Thing | Mar, 2021
Neural Networks

The “Blue Brain” Project-A mission to build a simulated Brain | by The A.I. Thing | Mar, 2021

April 17, 2021
Templates Vs Machine Learning OCR | by Infrrd | Mar, 2021
Neural Networks

Templates Vs Machine Learning OCR | by Infrrd | Mar, 2021

April 16, 2021
Artificial Intelligence in Radiology — Advantages, Use Cases & Trends | by ITRex Group | Apr, 2021
Neural Networks

Artificial Intelligence in Radiology — Advantages, Use Cases & Trends | by ITRex Group | Apr, 2021

April 16, 2021
A simple explanation of Machine Learning and Neural Networks and A New Perspective for ML Experts | by Akhilesh Ravi | Apr, 2021
Neural Networks

A simple explanation of Machine Learning and Neural Networks and A New Perspective for ML Experts | by Akhilesh Ravi | Apr, 2021

April 15, 2021
Next Post
Google Photos 5.18 lets you improve app’s machine learning

Google Photos 5.18 lets you improve app's machine learning

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Recommended

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

January 6, 2019
Microsoft, Google Use Artificial Intelligence to Fight Hackers

Microsoft, Google Use Artificial Intelligence to Fight Hackers

January 6, 2019

Categories

  • Artificial Intelligence
  • Big Data
  • Blockchain
  • Crypto News
  • Data Science
  • Digital Marketing
  • Internet Privacy
  • Internet Security
  • Learn to Code
  • Machine Learning
  • Marketing Technology
  • Neural Networks
  • Technology Companies

Don't miss it

SolarWinds cybersecurity spending tops $3 million in Q4, sees $20 million to $25 million in 2021
Internet Security

SolarWinds: US and UK blame Russian intelligence service hackers for major cyberattack

April 17, 2021
Machine learning can be your best bet to transform your career
Machine Learning

Machine learning can be your best bet to transform your career

April 17, 2021
AI and Human Rights, A Story About Equality | by bundleIQ | Mar, 2021
Neural Networks

AI and Human Rights, A Story About Equality | by bundleIQ | Mar, 2021

April 17, 2021
Monitor Your SEO Placement with SEObase
Learn to Code

Monitor Your SEO Placement with SEObase

April 17, 2021
Google Project Zero testing 30-day grace period on bug details to boost user patching
Internet Security

Google Project Zero testing 30-day grace period on bug details to boost user patching

April 17, 2021
Teslafan, a Blockchain-Powered Machine Learning Technology Project, Receives Investment Prior to the ICO
Machine Learning

Teslafan, a Blockchain-Powered Machine Learning Technology Project, Receives Investment Prior to the ICO

April 17, 2021
NikolaNews

NikolaNews.com is an online News Portal which aims to share news about blockchain, AI, Big Data, and Data Privacy and more!

What’s New Here?

  • SolarWinds: US and UK blame Russian intelligence service hackers for major cyberattack April 17, 2021
  • Machine learning can be your best bet to transform your career April 17, 2021
  • AI and Human Rights, A Story About Equality | by bundleIQ | Mar, 2021 April 17, 2021
  • Monitor Your SEO Placement with SEObase April 17, 2021

Subscribe to get more!

© 2019 NikolaNews.com - Global Tech Updates

No Result
View All Result
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News

© 2019 NikolaNews.com - Global Tech Updates