DenseLens - Using DenseNet ensembles and information criteria for finding and rank-ordering strong gravitational lenses
Sign Up to like & getrecommendations! Published in 2023 at "Monthly Notices of the Royal Astronomical Society"
DOI: 10.1093/mnras/stad1623
Abstract: Convolutional Neural Networks (CNNs) are the state-of-the-art technique for identifying strong gravitational lenses. Although they are highly successful in recovering genuine lens systems with a high true-positive rate, the unbalanced nature of the data set… read more here.
Keywords: strong gravitational; gravitational lenses; false positive; positive rates ... See more keywords
Finding strong gravitational lenses in the Kilo Degree Survey with Convolutional Neural Networks
Sign Up to like & getrecommendations! Published in 2017 at "Monthly Notices of the Royal Astronomical Society"
DOI: 10.1093/mnras/stx2052
Abstract: The volume of data that will be produced by new-generation surveys requires automatic classification methods to select and analyse sources. Indeed, this is the case for the search for strong gravitational lenses, where the population… read more here.
Keywords: strong gravitational; degree survey; kilo degree; convolutional neural ... See more keywords
Testing Convolutional Neural Networks for finding strong gravitational lenses in KiDS
Sign Up to like & getrecommendations! Published in 2018 at "Monthly Notices of the Royal Astronomical Society"
DOI: 10.1093/mnras/sty2683
Abstract: Convolutional Neural Networks (ConvNets) are one of the most promising methods for identifying strong gravitational lens candidates in survey data. We present two ConvNet lens-finders that we have trained with a dataset composed of real… read more here.
Keywords: strong gravitational; neural networks; convolutional neural; convnet ... See more keywords