Zobrazeno 1 - 10
of 1 344
pro vyhledávání: '"Suin A"'
Autor:
Ito, Kei, Tanaka, Takumi S., Shimasaku, Kazuhiro, Ando, Makoto, Onoue, Masafusa, Tanaka, Masayuki, Matsui, Suin, Kakimoto, Takumi, Valentino, Francesco
We report a characterization of an X-ray-detected quiescent galaxy at $z=2.09$, named COS-XQG1, using JWST/NIRCam and NIRSpec data. This galaxy is detected in Chandra imaging, suggesting the presence of an AGN with a high black hole accretion rate of
Externí odkaz:
http://arxiv.org/abs/2408.08492
This paper tackles the problem of motion deblurring of dynamic scenes. Although end-to-end fully convolutional designs have recently advanced the state-of-the-art in non-uniform motion deblurring, their performance-complexity trade-off is still sub-o
Externí odkaz:
http://arxiv.org/abs/2402.06117
Autor:
Suin, Maitreya, Chellappa, Rama
Recent generative-prior-based methods have shown promising blind face restoration performance. They usually project the degraded images to the latent space and then decode high-quality faces either by single-stage latent optimization or directly from
Externí odkaz:
http://arxiv.org/abs/2402.06106
Publikováno v:
MNRAS, Volume 529, Issue 2, April 2024, Pages 926-940
With an X-ray stacking analysis of ~ 12, 000 Lyman-break galaxies (LBGs) using the Chandra Legacy Survey image, we investigate average supermassive black hole (SMBH) accretion properties of star-forming galaxies (SFGs) at 4 <~ z <~ 7. Although no X-r
Externí odkaz:
http://arxiv.org/abs/2312.13651
To apply the latest computer vision techniques that require a large computational cost in real industrial applications, knowledge distillation methods (KDs) are essential. Existing logit-based KDs apply the constant temperature scaling to all samples
Externí odkaz:
http://arxiv.org/abs/2311.14334
Previous logits-based Knowledge Distillation (KD) have utilized predictions about multiple categories within each sample (i.e., class predictions) and have employed Kullback-Leibler (KL) divergence to reduce the discrepancy between the student and te
Externí odkaz:
http://arxiv.org/abs/2311.14307
Diffusion models have advanced generative AI significantly in terms of editing and creating naturalistic images. However, efficiently improving generated image quality is still of paramount interest. In this context, we propose a generic "naturalness
Externí odkaz:
http://arxiv.org/abs/2311.09753
Autor:
Tanaka, Takumi S., Shimasaku, Kazuhiro, Tacchella, Sandro, Ando, Makoto, Ito, Kei, Yesuf, Hassen M., Matsui, Suin
We present the HINOTORI (star formation History INvestigatiOn TO find RejuvenatIon) project to reveal the nature of rejuvenation galaxies (RGs), which are galaxies that restarted their star formation after being quiescent. As the first step of HINOTO
Externí odkaz:
http://arxiv.org/abs/2307.14235
Supervised networks address the task of low-light enhancement using paired images. However, collecting a wide variety of low-light/clean paired images is tedious as the scene needs to remain static during imaging. In this paper, we propose an unsuper
Externí odkaz:
http://arxiv.org/abs/2306.02883
Autor:
Gangbin Yan, Jialiang Wei, Emory Apodaca, Suin Choi, Peter J. Eng, Joanne E. Stubbs, Yu Han, Siqi Zou, Mrinal K. Bera, Ronghui Wu, Evguenia Karapetrova, Hua Zhou, Wei Chen, Chong Liu
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-13 (2024)
Abstract One-dimensional (1D) olivine iron phosphate (FePO4) is widely proposed for electrochemical lithium (Li) extraction from dilute water sources, however, significant variations in Li selectivity were observed for particles with different physic
Externí odkaz:
https://doaj.org/article/14334844fe754f10b1ded4d40212ea0c