VSOP: the variable star one-shot project
نویسندگان
چکیده
منابع مشابه
Variable-density one-shot Fourier velocity encoding.
In areas of highly pulsatile and turbulent flow, real-time imaging with high temporal, spatial, and velocity resolution is essential. The use of 1D Fourier velocity encoding (FVE) was previously demonstrated for velocity measurement in real time, with fewer effects resulting from off-resonance. The application of variable-density sampling is proposed to improve velocity measurement without a si...
متن کاملCSC 412/2506 Project: One-Shot Learning
Humans exhibit a strong ability to acquire and recognize new patterns. In particular, we observe that when presented with stimuli, people seem to be able to understand new concepts quickly and then recognize variations on these concepts in future percepts. Machine learning has been successfully used to achieve state-of-the-art performance in a variety of applications such as web search, spam de...
متن کاملGalactic and Extragalactic Distance Scales: The Variable Star Project
This paper summaries the status of a large project to improve distance scales of various classes of variable stars. This is being carried out by a large group in Cape Town, Japan, England and the USA. The results are illustrated by giving the distances to the Large Magellanic Cloud and the Galactic Centre (Ro) as well as the value of the Hubble Constant, Ho, based on our current results. The cl...
متن کاملOne-Shot Imitation Learning
Imitation learning has been commonly applied to solve different tasks in isolation. This usually requires either careful feature engineering, or a significant number of samples. This is far from what we desire: ideally, robots should be able to learn from very few demonstrations of any given task, and instantly generalize to new situations of the same task, without requiring task-specific engin...
متن کاملActive One-shot Learning
Recent advances in one-shot learning have produced models that can learn from a handful of labeled examples, for passive classification and regression tasks. This paper combines reinforcement learning with one-shot learning, allowing the model to decide, during classification, which examples are worth labeling. We introduce a classification task in which a stream of images are presented and, on...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Astronomy & Astrophysics
سال: 2007
ISSN: 0004-6361,1432-0746
DOI: 10.1051/0004-6361:20077571