Zobrazeno 1 - 10
of 4 978
pro vyhledávání: '"A. Mcreynolds"'
Biologically inspired event-based vision sensors (EVS) are growing in popularity due to performance benefits including ultra-low power consumption, high dynamic range, data sparsity, and fast temporal response. They efficiently encode dynamic informa
Externí odkaz:
http://arxiv.org/abs/2404.07656
Autor:
Birrell, Eleanor, Rodolitz, Jay, Ding, Angel, Lee, Jenna, McReynolds, Emily, Hutson, Jevan, Lerner, Ada
Growing recognition of the potential for exploitation of personal data and of the shortcomings of prior privacy regimes has led to the passage of a multitude of new online privacy regulations. Some of these laws -- notably the European Union's Genera
Externí odkaz:
http://arxiv.org/abs/2312.15383
Autor:
Golich, Milana, McReynolds, D. B.
We establish an analog of a theorem of Stallings which asserts the homomorphisms between the universal nilpotent quotients induced by a homomorphism $G \to H$ of groups are isomorphisms provided a pair of homological conditions are satisfied. Our ana
Externí odkaz:
http://arxiv.org/abs/2310.08283
The operation of the DVS event camera is controlled by the user through adjusting different bias parameters. These biases affect the response of the camera by controlling - among other parameters - the bandwidth, sensitivity, and maximum firing rate
Externí odkaz:
http://arxiv.org/abs/2304.04706
Under dim lighting conditions, the output of Dynamic Vision Sensor (DVS) event cameras is strongly affected by noise. Photon and electron shot-noise cause a high rate of non-informative events that reduce Signal to Noise ratio. DVS noise performance
Externí odkaz:
http://arxiv.org/abs/2304.04019
Dynamic Vision Sensors (DVS) record "events" corresponding to pixel-level brightness changes, resulting in data-efficient representation of a dynamic visual scene. As DVS expand into increasingly diverse applications, non-ideal behaviors in their out
Externí odkaz:
http://arxiv.org/abs/2304.03494
Inspired by work of Besson-Courtois-Gallot, we construct a flow called the natural flow on a nonpositively curved Riemannian manifold $M$. As with the natural map, the $k$-Jacobian of the natural flow is directly related to the critical exponent $\de
Externí odkaz:
http://arxiv.org/abs/2302.12665
Autor:
Svenja Kastellan, Reinhard Kalb, Bia Sajjad, Lisa J. McReynolds, Neelam Giri, David Samuel, Till Milde, Miriam Elbracht, Susanne Holzhauer, Marena R. Niewisch, Christian P. Kratz
Publikováno v:
Journal of Hematology & Oncology, Vol 17, Iss 1, Pp 1-5 (2024)
Abstract Constitutional heterozygous pathogenic variants in genes coding for some components of the Fanconi anemia-BRCA signaling pathway, which repairs DNA interstrand crosslinks, represent risk factors for common cancers, including breast, ovarian,
Externí odkaz:
https://doaj.org/article/f65bbdcf430341eb9cdd14a176000ac5
Autor:
Hazirbas, Caner, Bang, Yejin, Yu, Tiezheng, Assar, Parisa, Porgali, Bilal, Albiero, Vítor, Hermanek, Stefan, Pan, Jacqueline, McReynolds, Emily, Bogen, Miranda, Fung, Pascale, Ferrer, Cristian Canton
Developing robust and fair AI systems require datasets with comprehensive set of labels that can help ensure the validity and legitimacy of relevant measurements. Recent efforts, therefore, focus on collecting person-related datasets that have carefu
Externí odkaz:
http://arxiv.org/abs/2211.05809
Autor:
Zhao, Zhuowen, Chavez, Tanny, Holman, Elizabeth A., Hao, Guanhua, Green, Adam, Krishnan, Harinarayan, McReynolds, Dylan, Pandolfi, Ronald, Roberts, Eric J., Zwart, Petrus H., Yanxon, Howard, Schwarz, Nicholas, Sankaranarayanan, Subramanian, Kalinin, Sergei V., Mehta, Apurva, Campbell, Stuart, Hexemer, Alexander
Publikováno v:
2022 4th IEEE/ACM Annual Workshop on Extreme-scale Experiment-in-the-Loop Computing (XLOOP)
Machine learning (ML) algorithms are showing a growing trend in helping the scientific communities across different disciplines and institutions to address large and diverse data problems. However, many available ML tools are programmatically demandi
Externí odkaz:
http://arxiv.org/abs/2208.09751