Opendata, web and dolomites

SensifAI SIGNED

Understanding Videos Automatically with the SensifAI Deep Learning Technology

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 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.

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

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.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "SENSIFAI" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

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

More projects from the same programme (H2020-EU.3.;H2020-EU.2.3.;H2020-EU.2.1.)

Preemie (2019)

Personalised nutrition of low-birth-weight infants

Read More  

Proteus 25 (2018)

Developing the world’s first food wrapping machine with organic film

Read More  

Savesight (2020)

Contact lens embedded sensor for ocular hypertension and glaucoma monitoring

Read More