Related papers: A Semi-Automated Computational Approach for Infrar…
[Abridged] Though the exact role of infrared dark clouds in the formation process is still somewhat unclear, they seem to provide useful laboratories to study the very early stages of clustered star formation. Infrared dark clouds have been…
Context: The VISTA Variables in the Via Lactea (VVV) and its extension (VVVX) are near-infrared surveys mapping the Galactic bulge and adjacent disk. These data have enabled the discovery of numerous star clusters obscured by high and…
We generalize the technique of Lada et al. (1994) to map dust column density through a molecular cloud (NICE) to an optimized multi-band technique (NICER) that can be applied to any multi-band survey of molecular clouds. We present a first…
Infrared dark clouds (IRDCs) are fruitful objects to study the fragmentation of interstellar filaments and initial conditions and early stages of high-mass ($M>8$ M$_{\odot}$) star formation. We used the Yebes 40 m and IRAM 30 m radio…
For crowded scenes, the accuracy of object-based computer vision methods declines when the images are low-resolution and objects have severe occlusions. Taking counting methods for example, almost all the recent state-of-the-art counting…
We examine the physical properties and evolutionary stages of a sample of 17 clumps within 8 Infrared Dark Clouds (IRDCs) by combining existing infrared, millimeter, and radio data with new Bolocam Galactic Plane Survey (BGPS) 1.1 mm data,…
With the development of deep learning, many state-of-the-art natural image scene classification methods have demonstrated impressive performance. While the current convolution neural network tends to extract global features and global…
Clouds and snow have similar spectral features in the visible and near-infrared (VNIR) range and are thus difficult to distinguish from each other in high resolution VNIR images. We address this issue by introducing a shortwave-infrared…
Using three newly identified galaxy clusters at z~1 (photometric redshift) we measure the evolution of the galaxies within clusters from high redshift to the present day by studying the growth of the red cluster sequence. The clusters are…
Compact stellar systems such as Ultra-compact dwarfs (UCDs) and Globular Clusters (GCs) around galaxies are known to be the tracers of the merger events that have been forming these galaxies. Therefore, identifying such systems allows to…
Identified as extinction features against the bright Galactic mid-infrared background, infrared dark clouds (IRDCs) are thought to harbor the very earliest stages of star and cluster formation. In order to better characterize the properties…
The Red-Sequence Cluster Survey (RCS) is a $\sim$100 square degree, two-filter imaging survey in the $R_C$ and $z'$ filters, designed primarily to locate and characterise galaxy clusters to redshifts as high as $z=1.4$. This paper provides…
Deep graph clustering, which aims to reveal the underlying graph structure and divide the nodes into different clusters without human annotations, is a fundamental yet challenging task. However, we observed that the existing methods suffer…
Spitzer IRAC selection is a powerful tool for identifying luminous AGN. For deep IRAC data, however, the AGN selection wedges currently in use are heavily contaminated by star-forming galaxies, especially at high redshift. Using the large…
Hashing has been widely used in approximate nearest search for large-scale database retrieval for its computation and storage efficiency. Deep hashing, which devises convolutional neural network architecture to exploit and extract the…
We propose a deep convolutional neural network (CNN) for face detection leveraging on facial attributes based supervision. We observe a phenomenon that part detectors emerge within CNN trained to classify attributes from uncropped face…
We present new deep near-infrared images of dark clouds in the Perseus molecular complex. These images show beautiful extended emission which we model as scattered ambient starlight and name ``cloudshine''. The brightness and color…
Infrared (IR) imaging has the potential to enable more robust action recognition systems compared to visible spectrum cameras due to lower sensitivity to lighting conditions and appearance variability. While the action recognition task on…
Detecting and identifying objects in satellite images is a very challenging task: objects of interest are often very small and features can be difficult to recognize even using very high resolution imagery. For most applications, this…
3D tomography of the interstellar dust and gas may be useful in many respects, from the physical and chemical evolution of the ISM itself to foreground decontamination of the CMB, or various studies of the environments of specific objects.…