Specimen Preparation and Presentation

Bertin, Éric

doi:10.1007/978-1-4899-2204-5_10

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…Instead of designing a fine-tuned, classical algorithm to do the job, a new technique has been applied based on neural networks, a kind of "artificial retina". The details of this "retina" are described elsewhere (Bertin 1999), but it suffices to say here that it acts as a non-linear filter whose characteristics are set through machine-learning on a set of examples. The learning is conducted on pairs of images: one is the input image, the other is a "model", which is what one would like the input image to look like after filtering.…”

Section: Identification Of Electronic Artifactsmentioning

confidence: 99%

ESO Imaging Survey

Nonino

Bertin

Costa

et al. 1999

Astron. Astrophys. Suppl. Ser.

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Abstract. This paper presents the first data evaluation of the ESO Imaging Survey (EIS), a public survey being carried out by ESO and member states, in preparation for the VLT first-light. The survey goals, organization, strategy and observations are discussed and an overview is given of the survey pipeline developed to handle EIS data and produce object catalogs. A report is presented on moderately deep I-band observations obtained in the first of four patches surveyed, covering a region of 3.2 square degrees centered at α ∼ 22 h 40 m and δ = −40• . The products available to the community, including pixel maps (with astrometric and photometric calibrations) and the corresponding object catalogs, are also described. In order to evaluate the quality of the data, preliminary estimates are presented for the star and galaxy number counts, and for the angular two-point correlation function obtained from the available data. The present work is meant as a preview of the final release of the EIS data that will become available later this year.

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Section: Identification Of Electronic Artifactsmentioning

confidence: 99%