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A multi-class convolutional neural network (CNN) model has been developed using Keras deep learning library in Python for image-based classification of $^{12}$C Hoyle state decay branches from tracking information, recorded by Saha Active…
We propose a weakly-supervised framework for the semantic segmentation of circular-scan synthetic-aperture-sonar (CSAS) imagery. The first part of our framework is trained in a supervised manner, on image-level labels, to uncover a set of…
Studying CMEs in coronagraph data can be challenging due to their diffuse structure and transient nature, and user-specific biases may be introduced through visual inspection of the images. The large amount of data available from the SOHO,…
We present intensity-corrected Herschel maps at 100 um, 160 um, 250 um, 350 um, and 500 um for 56 isolated low-mass clouds. We determine the zero-point corrections for Herschel PACS and SPIRE maps from the Herschel Science Archive (HSA)…
Excessive or inadequate exposure to ultraviolet light (UV) is harmful to health and causes osteoporosis, colon cancer, and skin cancer. The UV Index, a standard scale of UV light, tends to increase in sunny places and sharply decrease in…
(abridged) Stellar catalogues in five passbands (UBVRI) over an area of approximately 0.3 deg^2, comprising about 1200 objects, and in seven passbands (UBVRIJK) over approximately 0.1 deg^2, comprising about 400 objects, in the direction of…
Aims. We calibrate the number density, completeness, reliability and the lower mass limit of galaxy-cluster detections through their thermal SZ signal, and compare them to X-ray cluster detections. Methods. We simulate maps of the thermal…
We have measured the root-mean-square (RMS) amplitude of intensity fluctuations, $\Delta I$, in plume and interplume regions of a polar coronal hole. These intensity fluctuations correspond to density fluctuations. Using data from the…
To enable a deep learning-based system to be used in the medical domain as a computer-aided diagnosis system, it is essential to not only classify diseases but also present the locations of the diseases. However, collecting instance-level…
Structural Health Monitoring (SHM) is a sustainable and essential approach for infrastructure maintenance, enabling the early detection of structural defects. Leveraging computer vision (CV) methods for automated infrastructure monitoring…
This paper presents a fully-automated method for the identification of suspicious regions of a coronavirus disease (COVID-19) on chest CT volumes. One major role of chest CT scanning in COVID-19 diagnoses is identification of an…
On modern satellite observations of the Sun in the continuum with high spatial resolution, as well as on high-quality ground observations, a large number of small dark areas can be observed. These regions have no penumbra, have a contrast…
We present a cosmic shear analysis of the 100 square degree weak lensing survey, combining data from the CFHTLS-Wide, RCS, VIRMOS-DESCART and GaBoDS surveys. Spanning ~100 square degrees, with a median source redshift z~0.78, this combined…
We perform an ensemble of $N$-body simulations with $2048^3$ particles for 101 flat $w$CDM cosmological models sampled based on a maximin-distance Sliced Latin Hypercube Design. By using the halo catalogs extracted at multiple redshifts in…
A method of synoptic map assimilation has been developed to study global rearrangements of open magnetic flux and formation of polar coronal holes (PCHs) in the current cycle. The analysis reveals ensembles of coronal holes (ECHs) which…
In hyperspectral remote sensing field, some downstream dense prediction tasks, such as semantic segmentation (SS) and change detection (CD), rely on supervised learning to improve model performance and require a large amount of manually…
With excellent angular resolution, good energy resolution and broad energy band, the Chandra ACIS is the best instrument for studying the X-ray halos around some galactic X-ray point sources caused by the dust scattering of X-rays in the…
The rapidly growing statistical precision of galaxy surveys has lead to a need for ever-more precise predictions of the observables used to constrain cosmological and galaxy formation models. The primary avenue through which such…
With the advent of deep learning for computer vision tasks, the need for accurately labeled data in large volumes is vital for any application. The increasingly available large amounts of solar image data generated by the Solar Dynamic…
We introduce the concept of a Background-subtracted Solar Activity Map (BaSAM) as a new quantitative tool to assess and visualize the temporal variation of the photospheric magnetic field and the UV 160 nm intensity. The method utilizes…