首页|Investigators at New York University (NYU) Describe Findings in Machine Learning (Notplanet: Removing False Positives From Planet Hunters Tess With Machine Lear ning)
Investigators at New York University (NYU) Describe Findings in Machine Learning (Notplanet: Removing False Positives From Planet Hunters Tess With Machine Lear ning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – A new study on Machine Learning is now available. According to news reporting fromNew York City, New York, by NewsRx journalists, research stated, “Differentiating between real transit events and f alse-positive signals in photometric time-series data is a bottleneck in the ide ntificationof transiting exoplanets, particularly long-period planets. This dif ferentiation typically requires visualinspection of a large number of transit-l ike signals to rule out instrumental and astrophysical false positivesthat mimi c planetary transit signals.”
New York CityNew YorkUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningNew York University (NYU)
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