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.

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

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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