相关论文: Capivara: A Spectral-based Segmentation Method for…
Hydrodynamic simulations are powerful tools for studying galaxy formation. However, it is crucial to test and improve the sub-grid physics underlying these simulations by comparing their predictions with observations. To this aim,…
The Magellan InfraRed Multi-Object Spectrograph (MIRMOS) is a planned next generation multi-object and integral field spectrograph for the 6.5m Magellan telescopes at Las Campanas Observatory in Chile. MIRMOS will perform R$\sim$3700…
Integral Field Spectroscopy (IFS) is an observational method to obtain spatially resolved spectra over a specific field of view (FoV) in a single exposure. In recent years, near-infrared IFS has gained importance in observing objects with…
With the rise of the integral field spectroscopy, we are currently dealing with large amounts of spatially resolved data, whose analysis has become challenging, especially when observing complex objects such as nearby galaxies. We aim to…
We present MUFFIT, a new generic code optimized to retrieve the main stellar population parameters of galaxies in photometric multi-filter surveys, and we check its reliability and feasibility with real galaxy data from the ALHAMBRA survey.…
This paper proposes a spatial feature extraction method based on energy of the features for classification of the hyperspectral data. A proposed orthogonal filter set extracts spatial features with maximum energy from the principal…
We present infrared aperture synthesis maps produced with the upgraded IOTA interferometer. Michelson interferograms on the close binary system Capella (Alpha Aur) were obtained in the H-band between 2002 November 12 and 16 using the IONIC3…
Aims: To investigate the characteristics of the bar and inner disk in the collisional ring galaxy Cartwheel. Methods: We used the Integral Field Unit (IFU) observations with Multi-Unit Spectroscopic Explorer (MUSE) of the Very Large…
Semantic segmentation and object detection research have recently achieved rapid progress. However, the former task has no notion of different instances of the same object, and the latter operates at a coarse, bounding-box level. We propose…
Infrared and visible dual-modality tasks such as semantic segmentation and object detection can achieve robust performance even in extreme scenes by fusing complementary information. Most current methods design task-specific frameworks,…
MaNGA (Mapping Nearby Galaxies at Apache Point Observatory) is an integral-field spectroscopic survey of 10,000 nearby galaxies that is one of three core programs in the fourth-generation Sloan Digital Sky Survey (SDSS-IV). MaNGA's 17…
Collective insights from a group of experts have always proven to outperform an individual's best diagnostic for clinical tasks. For the task of medical image segmentation, existing research on AI-based alternatives focuses more on…
In this paper we describe the FIT\textit{spec} code, a data mining tool for the automatic fitting of synthetic stellar spectra. The program uses a database of 27\,000 {\sc cmfgen} models of stellar atmospheres arranged in a six-dimensional…
The statistical description of Giant Molecular Cloud (GMC) properties relies heavily on the performance of automatic identification algorithms, which are often seriously affected by the survey design. The algorithm we designed, SCIMES…
In this paper we propose a new efficient interpolation tool, extremely suitable for large scattered data sets. The partition of unity method is used and performed by blending Radial Basis Functions (RBFs) as local approximants and using…
Accurate diagnosis of glaucoma is challenging, as early-stage changes are subtle and often lack clear structural or appearance cues. Most existing approaches rely on a single modality, such as fundus or optical coherence tomography (OCT),…
Humans tend to mine objects by learning from a group of images or several frames of video since we live in a dynamic world. In the computer vision area, many researches focus on co-segmentation (CoS), co-saliency detection (CoSD) and video…
Intra-pixel sensitivity variations (IPSVs) in charge-coupled devices (CCDs) and complementary metal-oxide-semiconductor (CMOS) detectors constitute a significant source of astrometric error for undersampled stellar observations. Since…
The latest generation of radio astronomy interferometers will conduct all sky surveys with data products consisting of petabytes of spectral line data. Traditional approaches to identifying and parameterising the astrophysical sources…
We present a novel unsupervised learning approach to automatically segment and label images in astronomical surveys. Automation of this procedure will be essential as next-generation surveys enter the petabyte scale: data volumes will…