RTOBJECTS
We transform the way brands sell and tell stories online with Personal Interactive CGI. Everyone buys online – digital is replacing the retail experience. Buying online provides amazing convenience, choice and control. But online product visuals are static, inflexible and lifeless – nowhere near the retail experience. We combine the rich cinematic visuals of games and movies with the interactivity of the Internet to deliver Personal Interactive CGI. We deliver these interactive visual experiences in standard web pages, on any device - no downloads, no wait times. So people can really see and experience things before they buy them.
RTOBJECTS
Social Links:
Industry:
Advertising Automotive Cloud Computing Data Visualization Digital Marketing E-Commerce Gaming Real Estate Video Streaming Virtual Reality
Founded:
2015-11-16
Address:
London, England, United Kingdom
Country:
United Kingdom
Website Url:
http://www.rtobjects.com
Total Employee:
1+
Status:
Closed
Email Addresses:
[email protected]
Total Funding:
150 K USD
Technology used in webpage:
SSL By Default Apple Mobile Web Clips Icon Domain Not Resolving CloudFront Ubuntu Ruby On Rails Token Amazon Ireland Region
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Collider investment in Pre Seed Round - rtobjects
More informations about "rtobjects"
[2009.07586] Optimising and comparing source extraction tools using objective segmentation quality criteria
GitHub - CarolineHaigh/mtobjects: Development …
MTObjects is a tool for detecting sources in astronomical images, and creating segmentation maps and parameter tables. This is a work in progress - use at your own risk. Questions, bug reports, and suggested features are very welcome.See details»
[2211.12809] A comparative study of source-finding techniques in …
Nov 23, 2022 · Two traditional source-finding methods were tested, SoFiA and MTObjects, as well as a new supervised deep learning approach, in which a 3D convolutional neural network …See details»
Optimising and comparing source-extraction tools using objective ...
Jan 1, 2021 · Aims: We present a comparison of several tools developed to perform this task: namely SExtractor, ProFound, NoiseChisel, and MTObjects. In particular, we focus on …See details»
Optimising and comparing source extraction tools using objective ...
Sep 16, 2020 · We present a comparison of several tools which have been developed to perform this task: namely SExtractor, ProFound, NoiseChisel, and MTObjects.See details»
Optimising and comparing source-extraction tools using objective ...
Summary of qualitative evaluation. Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the …See details»
Optimising and comparing source-extraction tools using objective ...
Jan 22, 2021 · We present a comparison of several tools developed to perform this task: namely SExtractor, ProFound, NoiseChisel, and MTObjects. In particular, we focus on evaluating …See details»
NoiseChisel and MTObjects (detection, Mohammad, Aku & Caroline)
Peaks: MTObjects segmentation map. For an easier visual comparison on the actual image, a circular aperture (of xed size) is placed at the central position of each detected peak over the …See details»
Optimising and comparing source-extraction tools using objective ...
We present a comparison of several tools developed to perform this task: namely SExtractor, ProFound, NoiseChisel, and MTObjects. In particular, we focus on evaluating performance in …See details»
mtobjects/mtolib/src/mt_objects.c at master - GitHub
Development version of mtobjects, a tool for finding objects in astronomical images. - CarolineHaigh/mtobjectsSee details»
A comparative study of source-finding techniques in HI emission …
Two traditional source-finding methods were tested first: the well-established H i source-finding software SoFiA and one. of the most recent, best performing optical source-finding pieces of …See details»
Optimising and comparing source-extraction tools using objective ...
MTObjects achieves the highest scores on all tests for all four quality measures, whilst SExtractor obtains the highest speeds. No tool has sufficient speed and accuracy to be well suited to …See details»
GitHub - FimomilI/python-mtobjects: Development version of …
MTObjects is a tool for detecting sources in astronomical images, and creating segmentation maps and parameter tables. This is a work in progress - use at your own risk. Questions, bug …See details»
Optimising and comparing source-extraction tools using objective ...
Nov 13, 2020 · We present a comparison of several tools developed to perform this task: namely SExtractor, ProFound, NoiseChisel, and MTObjects. In particular, we focus on evaluating …See details»
A comparative study of source-finding techniques in HI emission …
Nov 22, 2022 · Two traditional source-finding methods were tested first: the well-established H I source-finding software SoFiA and one of the most recent, best performing optical source …See details»
A comparative study of source-finding techniques in H - aanda.org
Feb 3, 2023 · Two traditional source-finding methods were tested first: the well-established H I source-finding software SoFiA and one of the most recent, best performing optical source …See details»
mtobjects/mtolib/io_mto.py at master · CarolineHaigh/mtobjects
Development version of mtobjects, a tool for finding objects in astronomical images. - mtobjects/mtolib/io_mto.py at master · CarolineHaigh/mtobjectsSee details»
Schematic diagram of the source-finding pipeline of MTObjects …
Download scientific diagram | Schematic diagram of the source-finding pipeline of MTObjects (Arnoldus 2015). An H i emission sub-cube, which contains a source, is transformed into a …See details»
Problème de compilation avec une bibliothèque - Arduino Forum
Sep 7, 2022 · Pour régler ce genre de problème facilement, il y a deux possibilités : La première est de repasser à l'ancienne version. Mais uniquement si la deuxième solution ne fonctionne …See details»
MTObjects identiies better fainter outer regions and the nested ...
Two traditional source-finding methods were tested, SoFiA and MTObjects, as well as a new supervised deep learning approach, in which a 3D convolutional neural network architecture, …See details»