Zobrazeno 1 - 10
of 749
pro vyhledávání: '"Zhou, Kevin A."'
Autor:
Zhou, Kevin, Brauner, Tomas
Electric fields are commonly visualized with field line diagrams, which only unambiguously specify the field's direction. We consider two simple questions. First, can one deduce if an electric field is conservative, as required e.g. in electrostatics
Externí odkaz:
http://arxiv.org/abs/2411.08283
Autor:
Kreiss, Lucas, Tang, Weiheng, Balla, Ramana, Yang, Xi, Chaware, Amey, Kim, Kanghyun, Cook, Clare B., Begue, Aurelien, Dugo, Clay, Harfouche, Mark, Zhou, Kevin C., Horstmeyer, Roarke
We present an approach of utilizing a multi-camera array system for capturing dynamic high-resolution videos of the human face, with improved imaging performance as compared to traditional single-camera configurations. Employing an array of 54 indivi
Externí odkaz:
http://arxiv.org/abs/2410.01973
Autor:
Kim, Kanghyun, Chaware, Amey, Cook, Clare B., Xu, Shiqi, Abdelmalak, Monica, Cooke, Colin, Zhou, Kevin C., Harfouche, Mark, Reamey, Paul, Saliu, Veton, Doman, Jed, Dugo, Clay, Horstmeyer, Gregor, Davis, Richard, Taylor-Cho, Ian, Foo, Wen-Chi, Kreiss, Lucas, Jiang, Xiaoyin Sara, Horstmeyer, Roarke
Optical microscopy has long been the standard method for diagnosis in cytopathology. Whole slide scanners can image and digitize large sample areas automatically, but are slow, expensive and therefore not widely available. Clinical diagnosis of cytol
Externí odkaz:
http://arxiv.org/abs/2409.15722
Autor:
Zhou, Kevin
Learning automata by queries is a long-studied area initiated by Angluin in 1987 with the introduction of the $L^*$ algorithm to learn regular languages, with a large body of work afterwards on many different variations and generalizations of DFAs. R
Externí odkaz:
http://arxiv.org/abs/2409.10822
Autor:
Bates, Blake, Berikkyzy, Zhanar, Chiem, Nick, Elvin, Gabriel, Fines, Risa, Lie, Maja, Mikulás, Hanna, Reiter, Isaac, Zhou, Kevin
We say a graph $H$ is $r$-rainbow-uncommon if the maximum number of rainbow copies of $H$ under an $r$-coloring of $E(K_n)$ is asymptotically (as $n \to \infty$) greater than what is expected from uniformly random $r$-colorings. Via explicit construc
Externí odkaz:
http://arxiv.org/abs/2403.04055
Publikováno v:
JHEP 05 (2024) 314
In the presence of axion dark matter, fermion spins experience an "axion wind" torque and an "axioelectric" force. We investigate new experimental probes of these effects and find that magnetized analogs of multilayer dielectric haloscopes can explor
Externí odkaz:
http://arxiv.org/abs/2312.11601
Autor:
Zhou, Kevin C., Harfouche, Mark, Zheng, Maxwell, Jönsson, Joakim, Lee, Kyung Chul, Appel, Ron, Reamey, Paul, Doman, Thomas, Saliu, Veton, Horstmeyer, Gregor, Horstmeyer, Roarke
We present a large-scale computational 3D topographic microscope that enables 6-gigapixel profilometric 3D imaging at micron-scale resolution across $>$110 cm$^2$ areas over multi-millimeter axial ranges. Our computational microscope, termed STARCAM
Externí odkaz:
http://arxiv.org/abs/2306.02634
While distributional reinforcement learning (DistRL) has been empirically effective, the question of when and why it is better than vanilla, non-distributional RL has remained unanswered. This paper explains the benefits of DistRL through the lens of
Externí odkaz:
http://arxiv.org/abs/2305.15703
Autor:
Xu, Shiqi, Dai, Xiang, Ritter, Paul, Lee, Kyung Chul, Yang, Xi, Kreiss, Lucas, Zhou, Kevin C., Kim, Kanghyun, Chaware, Amey, Neff, Jadee, Glass, Carolyn, Lee, Seung Ah, Friedrich, Oliver, Horstmeyer, Roarke
Publikováno v:
Tensorial tomographic Fourier Ptychography with applications to muscle tissue imaging, Adv. Photon. 6(2), 026004 (2024)
We report Tensorial tomographic Fourier Ptychography (ToFu), a new non-scanning label-free tomographic microscopy method for simultaneous imaging of quantitative phase and anisotropic specimen information in 3D. Built upon Fourier Ptychography, a qua
Externí odkaz:
http://arxiv.org/abs/2305.05085
Dataset expansion can effectively alleviate the problem of data scarcity for medical image segmentation, due to privacy concerns and labeling difficulties. However, existing expansion algorithms still face great challenges due to their inability of g
Externí odkaz:
http://arxiv.org/abs/2304.13416