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.

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

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.)

Colourganisms (2020)

Microbial production of custom-made, pure and sustainable anthocyanins

Read More  

TAPPXSSAI (2019)

Development of a system for automatic ad insertion into on-demand streaming video to provide new monetization mechanisms to the media industry

Read More  

LTS (2020)

LEARNING TO SLEEP: INCREASING HEALTH THROUGH BETTER SLEEP

Read More