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The Picture Pile Platform

There has been tremendous progress in artificial intelligence (AI) in many different fields due to improved machine learning algorithms, advances in computing power and the availability of big data. With machine learning platforms... ver más

30/06/2023

IIASA

150K€

Presupuesto del proyecto: 150K€

Líder del proyecto

INTERNATIONALES INSTITUT FUER ANGEWANDTE SYST... No se ha especificado una descripción o un objeto social para esta compañía.

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Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2023-06-30

ERC-2020-POC: Call for proposals for ERC Proof of...

I+D

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No hay información privada compartida para este proyecto. Habla con el coordinador.

2 Participantes

IIASA

150.00K€ | Lider

FERTIBERIA

578.65K€ | Participante

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Duración del proyecto: 27 meses Fecha Inicio: 2021-03-25
Fecha Fin: 2023-06-30

Líder del proyecto

INTERNATIONALES INSTITUT FUER ANGEWANDTE SYST... No se ha especificado una descripción o un objeto social para esta compañía.

Presupuesto del proyecto 150K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto There has been tremendous progress in artificial intelligence (AI) in many different fields due to improved machine learning algorithms, advances in computing power and the availability of big data. With machine learning platforms like TensorFlow (Google), PyTorch (Facebook), Azure (Microsoft) or CoreML (Apple), researchers and application developers can now use AI for applications such as computer vision. While there are many image databases available such as Imagenet, which can be used to train machine learning algorithms to recognize a set of generic categories, e.g., cats, there is still a lack of image databases containing more specific features of interest, e.g., crop types. Moreover, there is currently no platform that offers a streamlined, standardized approach to setting up and running an image classification campaign to ingest the millions of photographs currently collected by many people around the world. The value proposition of the ERC PoC Picture Pile Platform (PPP) is to develop an innovative, commercially self-sustaining platform that uses the crowdsourcing game Picture Pile to rapidly classify images for machine learning purposes. After a pile of images has been sorted, the image classifications will be made publicly available. A number of premium services will be added to the Picture Pile Platform, which will make the platform self-sustaining. Campaign creators will be able to pay the crowd (with a small share paid to the Picture Pile Platform) for sorting the images. Paid advertisements will be possible through our social media channels as well as paid for space on the main Picture Pile page to attract more users. For a small fee, users will be able to use the Picture Pile Cloud for specific computer vision tasks using the machine learning models that will be built and trained with the Picture Pile data sets. The Picture Pile Platform has the potential to become a self-sustaining hub for crowdsourcing image classifications for machine learning.

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