Radial distribution of stars, gas and dust in SINGS galaxies. I. Surface photometry and morphology

We present ultraviolet through far-infrared surface brightness profiles for the 75 galaxies in the Spitzer Infrared Nearby Galaxies Survey (SINGS). The imagery used to measure the profiles includes GALEX UV data, optical images from KPNO, CTIO and SDSS, near-IR data from 2MASS, and mid- and far-infrared images from Spitzer. Along with the radial profiles, we also provide multi-wavelength asymptotic magnitudes and several non-parametric indicators of galaxy morphology: the concentration index (C_42), the asymmetry (A), the Gini coefficient (G) and the normalized second-order moment of the brightest 20% of the galaxy's flux (M_20). Our radial profiles show a wide range of morphologies and multiple components (bulges, exponential disks, inner and outer disk truncations, etc.) that vary not only from galaxy to galaxy but also with wavelength for a given object. In the optical and near-IR, the SINGS galaxies occupy the same regions in the C_42-A-G-M_20 parameter space as other normal galaxies in previous studies. However, they appear much less centrally concentrated, more asymmetric and with larger values of G when viewed in the UV (due to star-forming clumps scattered across the disk) and in the mid-IR (due to the emission of Polycyclic Aromatic Hydrocarbons at 8.0 microns and very hot dust at 24 microns).Comment: 66 pages in preprint format, 14 figures, published in ApJ. The definitive publisher authenticated version is available online at http://dx.doi.org/10.1088/0004-637X/703/2/156

Residual Spatial Fusion Network for RGB-Thermal Semantic Segmentation

Semantic segmentation plays an important role in widespread applications such as autonomous driving and robotic sensing. Traditional methods mostly use RGB images which are heavily affected by lighting conditions, \eg, darkness. Recent studies show thermal images are robust to the night scenario as a compensating modality for segmentation. However, existing works either simply fuse RGB-Thermal (RGB-T) images or adopt the encoder with the same structure for both the RGB stream and the thermal stream, which neglects the modality difference in segmentation under varying lighting conditions. Therefore, this work proposes a Residual Spatial Fusion Network (RSFNet) for RGB-T semantic segmentation. Specifically, we employ an asymmetric encoder to learn the compensating features of the RGB and the thermal images. To effectively fuse the dual-modality features, we generate the pseudo-labels by saliency detection to supervise the feature learning, and develop the Residual Spatial Fusion (RSF) module with structural re-parameterization to learn more promising features by spatially fusing the cross-modality features. RSF employs a hierarchical feature fusion to aggregate multi-level features, and applies the spatial weights with the residual connection to adaptively control the multi-spectral feature fusion by the confidence gate. Extensive experiments were carried out on two benchmarks, \ie, MFNet database and PST900 database. The results have shown the state-of-the-art segmentation performance of our method, which achieves a good balance between accuracy and speed

On the nature of the Herbig B[e] star binary system V921 Scorpii: Geometry and kinematics of the circumprimary disk on sub-AU scales

V921 Scorpii is a close binary system (separation 0.025") showing the B[e]-phenomenon. The system is surrounded by an enigmatic bipolar nebula, which might have been shaped by episodic mass-loss events, possibly triggered by dynamical interactions between the companion and the circumprimary disk (Kraus et al. 2012a). In this paper, we investigate the spatial structure and kinematics of the circumprimary disk, with the aim to obtain new insights into the still strongly debated evolutionary stage. For this purpose, we combine, for the first time, infrared spectro-interferometry (VLTI/AMBER, R=12,000) and spectro-astrometry (VLT/CRIRES, R=100,000), which allows us to study the AU-scale distribution of circumstellar gas and dust with an unprecedented velocity resolution of 3 km*s^-1. Using a model-independent photocenter analysis technique, we find that the Br-gamma-line emission rotates in the same plane as the dust disk. We can reproduce the wavelength-differential visibilities and phases and the double-peaked line profile using a Keplerian-rotating disk model. The derived mass of the central star is 5.4+/-0.4 M_sun*(d/1150 pc), which is considerably lower than expected from the spectral classification, suggesting that V921 Sco might be more distant (d approx 2kpc) than commonly assumed. Using the geometric information provided by our Br-gamma spectro-interferometric data and Paschen, Brackett, and Pfund line decrement measurements in 61 hydrogen recombination line transitions, we derive the density of the line-emitting gas (N_e=2...6*10^19 m^-3). Given that our measurements can be reproduced with a Keplerian velocity field without outflowing velocity component and the non-detection of age-indicating spectroscopic diagnostics, our study provides new evidence for the pre-main-sequence nature of V921 Sco.Comment: 17 pages, 11 figures, 3 tables, accepted by Ap

Learning Visual Context by Comparison

Finding diseases from an X-ray image is an important yet highly challenging task. Current methods for solving this task exploit various characteristics of the chest X-ray image, but one of the most important characteristics is still missing: the necessity of comparison between related regions in an image. In this paper, we present Attend-and-Compare Module (ACM) for capturing the difference between an object of interest and its corresponding context. We show that explicit difference modeling can be very helpful in tasks that require direct comparison between locations from afar. This module can be plugged into existing deep learning models. For evaluation, we apply our module to three chest X-ray recognition tasks and COCO object detection & segmentation tasks and observe consistent improvements across tasks. The code is available at https://github.com/mk-minchul/attend-and-compare.Comment: ECCV 2020 spotlight pape

A Study of H2 Emission in Three Bipolar Proto-Planetary Nebulae: IRAS 16594-4656, Hen 3-401, and Rob 22

We have carried out a spatial-kinematical study of three proto-planetary nebulae, IRAS 16594-4656, Hen 3-401, and Rob 22. High-resolution H2 images were obtained with NICMOS on the HST and high-resolution spectra were obtained with the Phoenix spectrograph on Gemini-South. IRAS 16594-4656 shows a "peanut-shaped" bipolar structure with H2 emission from the walls and from two pairs of more distant, point-symmetric faint blobs. The velocity structure shows the polar axis to be in the plane of the sky, contrary to the impression given by the more complex visual image and the visibility of the central star, with an ellipsoidal velocity structure. Hen 3-401 shows the H2 emission coming from the walls of the very elongated, open-ended lobes seen in visible light, along with a possible small disk around the star. The bipolar lobes appear to be tilted 10-15 deg with respect to the plane of the sky and their kinematics display a Hubble-like flow. In Rob 22, the H2 appears in the form of an "S" shape, approximately tracing out the similar pattern seen in the visible. H2 is especially seen at the ends of the lobes and at two opposite regions close to the unseen central star. The axis of the lobes is nearly in the plane of the sky. Expansion ages of the lobes are calculated to be approximately 1600 yr (IRAS 16594-4656), 1100 yr (Hen 3-401), and 640 yr (Rob 22), based upon approximate distances