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Google Dataset Search is a search engine from Google that helps researchers locate online data that is freely available for use. [1] The company launched the service on September 5, 2018, and stated that the product was targeted at scientists and data journalists. The service was out of beta as of January 23, 2020. [2]
Dialogue Systems Research 2015 [73] Lowe, R. et al. Dialog State Tracking Challenge The Dialog State Tracking Challenges 2 & 3 (DSTC2&3) were research challenge focused on improving the state of the art in tracking the state of spoken dialog systems. Transcription of spoken dialogs with labelling
Srinivasan e al, Google Research Visual Genome Images and their description 108,000 images, text Image captioning 2016 [12] R. Krishna et al. Berkeley 3-D Object Dataset 849 images taken in 75 different scenes. About 50 different object classes are labeled. Object bounding boxes and labeling. 849 labeled images, text Object recognition 2014 [13 ...
In contrast, the latest research focuses on young adults ages 21–25 – an important age group. Chronic diet-associated conditions, like type 2 diabetes or obesity, often take decades to develop ...
And research data from national surveys of American children called the “Youth Risk Behavioral Surveillance System” also wasn’t available on Friday.
Cognitively normal human brain samples collected at autopsy in early 2024 contained more tiny shards of plastic than samples collected eight years prior, according to a new study. Overall, cadaver ...
re3data.org is a global registry of research data repositories from all academic disciplines. It provides an overview of existing research data repositories in order to help researchers to identify a suitable repository for their data and thus comply with requirements set out in data policies. [1] [2] The registry went live in autumn 2012. [3]
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.