Opendata, web and dolomites

SensifAI SIGNED

Understanding Videos Automatically with the SensifAI Deep Learning Technology

Total Cost €

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EC-Contrib. €

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Partnership

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 SensifAI project word cloud

Explore the words cloud of the SensifAI project. It provides you a very rough idea of what is the project "SensifAI" about.

landmark    music    objects    international    video    helping    01    action    audios    visually    web    founded    scientists    eth    imaging    sensifai    05    people    became    tag    involvement    believe    surrounding    texts    contents    119    delivers    smartphones    camera    impaired    scene    cloud    scenes    amazon    limited    searchable    content       trillion    customized    audio    similarly    extremely    recognition    moods    visual    day    describing    imagine    unsafe    genre    accurately    cutting    alumni    contextual    traffic    captured    logos    80    semantic    follow    recognizing    starting    recognizes    model    bvba    images    videos    oem    emotion    mobile    manually    microphone    celebrities    million    speech    tags    edge    services    recognize    marketplace    google    landmarks    equipped    acquired    pricing    software    ku    europeans    automated    ranging    aurally    deep    automatically    actions    accumulative    sport    leuven    wearable    data    mit    millions    zurich    emerge    internet    trained    minute    learning    managed    description    environment    tagging   

Project "SensifAI" data sheet

The following table provides information about the project.

Coordinator
SENSIFAI 

Organization address
address: DREVE DE NIVELLES 182/9
city: BRUSSELS
postcode: 1160
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Belgium [BE]
 Project website https://sensifai.com/
 Total cost 71˙429 €
 EC max contribution 50˙000 € (70%)
 Programme 1. H2020-EU.3. (PRIORITY 'Societal challenges)
2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs)
3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies)
 Code Call H2020-SMEInst-2018-2020-1
 Funding Scheme SME-1
 Starting year 2018
 Duration (year-month-day) from 2018-12-01   to  2019-05-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    SENSIFAI BE (BRUSSELS) coordinator 50˙000.00

Map

 Project objective

Google has a value of $1 trillion because it has managed to make texts searchable. However, 80% of internet traffic is videos, audios and images and they are not searchable. Making videos searchable is extremely challenging. This is why most of the video tagging is done manually and the results in automated video recognition are still limited. Mobile video recognition is also starting to emerge. SensifAI has developed a cutting-edge audio-visual deep-learning technology trained on millions of videos to recognize audio and video content and to tag them accurately. SensifAI automatically tags videos, images and audio, which makes them searchable and can be customized for a range of use cases. We believe our approach to contextual video analysis is unique and on the leading edge as it recognizes, scenes, actions, celebrities, landmarks, logos, music genre, moods and emotion and speech. SensifAI delivers the video recognition technology on the cloud on the Amazon Web Services Marketplace and can be embedded on devices such as smartphones (by OEM’s). Our software just became available on the Amazon Web Services Marketplace where we follow a unit-based pricing model ranging from €0.01/minute for recognizing landmark images/objects/celebrities/unsafe contents to €0.05/minute for general tagging and action/sport recognition. SensifAI bvba was founded by three alumni and scientists from MIT, ETH Zurich and KU Leuven, who acquired an accumulative experience in audio-visual data processing through involvement in many international projects. Imagine a day when the 30 million visually impaired Europeans use a wearable camera equipped with a software describing them the surrounding environment automatically by recognizing the semantic concept of the captured video. includes the description of the scene, objects, and activities. Similarly, imaging a technology when the 119 million aurally impaired people use a wearable microphone equipped with a software helping them.

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The information about "SENSIFAI" are provided by the European Opendata Portal: CORDIS opendata.

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