machine learning for images

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1 Machine Learning for Images

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Post on 17-Jul-2015

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Machine Learning for Images

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Huge amountof user-generated

content

NOT searchable

NOT monetizable

It’s a big, big image world

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Image is a matrix of pixels (raster data)

What is specific: image recognition

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Recognition is sensitive to: lighting

contrast

saturation

blur

noise

What is specific: image recognition

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sensitive to

geometric transformations (scaling, translation, rotation)

occlusion

hard tofind optimal set of filters

What is specific: image recognition

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pixels lots of data themselvesin spatial relationships

multiple levels and scales of interestfrom low-level features such as texture to high-level features such as composition

needs data-augmentationcompensate for sensitivity - training with blurred, cropped, scaled, noised, etc

What is specific: ML for images

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huge architecture (both deep and wide) - requires massive amount of memory and processing power

inter- and intra-class varietyneed to describe the universe (huge and diverse datasets required to feed the data greedy CNNs)

takes time10+ days for large architectures, even after 10x reduction thanks to using GPUs

What is specific: ML for images

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cuda-convnet python interface, fermi-generation nVidia GPU, no multi-GPU support

cuda-convnet2an upgrade to cuda-convnet, optimized for new kepler-generation nVidia GPUs, multi-GPU support

caffedeep learning framework, developed by Berkeley Vision and Learning Center, big community of contributors

Convnet implementations for images

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torch7 ML algorithms, CNN extensions: fbcnn by Facebook, used by Google DeepMind

theanopython library, open-ended in terms of network architecture & transfer functions

…many others

Convnet implementations for images

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Imagga auto tagging

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CNN classifier with ~3000 everyday-life objects

Imagga Auto Tagging

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Expansion with semantically related concepts

Imagga Auto Tagging

business meeting presentation

laptop

desk

people

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semantic expansion ‘car’ -> ‘vehicle’ -> ‘mean of transportation’

feedback-loopinstant learning from user feedback, to be released in May

custom trainingwith specific set of tags

Imagga Auto Tagging

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What can be builtwith Image Recognition

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Personal Photo Applications

•Apps for mobile photos organization• Integration in telecom solutions•Cloud services for consumers•Device manufacturers

http://getsliki.com

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Integration with analytics platforms

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Image Processing Services

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(Stock) Photography

http://wordroom.org

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Big image data management and organization Image driven platforms (DAMs)

Contextual advertisingInteractive/behavioural campaigns (adSense like)

User profiling insight market, profiling based on image content

Interactive campaigns for brands new ways to interact with customers

Use Cases

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Imagga APIs

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Imagga API: How it works

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Sign Upwww.imagga.com

Free Hacker Planto try out our image tagging API

Developer Planany of the APIs & within larger limits

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ML Internship learn the AI magic

work with machine learningdata collectioninternal tool-chains

email us: [email protected]

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ML Meetup Sofiamachine learning meetups

bit.ly/mlmeetupSign Up

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Thank You

[email protected] twitter.com/imagga facebook.com/imagga