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Related papers: Optofluidic Force Induction as a Process Analytica…

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We propose and demonstrate a novel scheme for optical nanoparticle characterization, optofluidic force induction (OF2i), which achieves real-time optical counting with single-particle sensitivity, high throughput, and for particle sizes…

Optofluidic force induction (OF2i) is an optical nanoparticle characterization scheme which achieves real-time optical counting with single-particle sensitivity and high throughput. In a recent paper [\v{S}imi\'c et al., Phys. Rev. Appl.…

Optics · Physics 2023-02-07 Marko Šimić , Christian Hill , Ulrich Hohenester

High-Q optical resonators allow label-free detection of individual nanoparticles through perturbation of optical signatures but have practical limitations due to reliance on random diffusion to deliver particles to the sensing region. We…

Optics · Physics 2016-10-03 Jeewon Suh , Kewen Han , Christopher W Peterson , Gaurav Bahl

Optofluidics is dedicated to achieving integrated control of particle and fluid motion, particularly on the micrometer scale, by utilizing light to direct fluid flow and particle motion. The field has seen significant growth recently,…

Optical flow provides information on relative motion that is an important component in many computer vision pipelines. Neural networks provide high accuracy optical flow, yet their complexity is often prohibitive for application at the edge…

Computer Vision and Pattern Recognition · Computer Science 2023-07-13 Yannick Schnider , Stanislaw Wozniak , Mathias Gehrig , Jules Lecomte , Axel von Arnim , Luca Benini , Davide Scaramuzza , Angeliki Pantazi

Opto-mechano-fluidic resonators (OMFRs) are a new platform for high-throughput sensing of the mechanical properties of freely flowing microparticles in arbitrary media. Experimental extraction of OMFR mode shapes, especially the acoustic…

Optics · Physics 2018-03-14 Jeewon Suh , Kewen Han , Gaurav Bahl

Implementing optical-based memory and utilizing it for computation on the nanoscale remains an attractive but still a challenging task. While significant progress was achieved in nanophotonics, allowing to explore nonlinear optical effects…

Motion representation plays a vital role in human action recognition in videos. In this study, we introduce a novel compact motion representation for video action recognition, named Optical Flow guided Feature (OFF), which enables the…

Computer Vision and Pattern Recognition · Computer Science 2018-07-10 Shuyang Sun , Zhanghui Kuang , Wanli Ouyang , Lu Sheng , Wei Zhang

We introduce a method for analyzing the physical properties of nanoparticles in fluids via the competition between viscous drag and optical forces. By flowing particles through a microfluidic device containing an optical microcavity which…

Optics · Physics 2021-12-01 Kiana Malmir , William Okell , Aurélien A P Trichet , Jason M Smith

Manipulating fluids by light at the nanoscale has been a long-sought-after goal for lab-on-a-chip applications. Plasmonic heating has been demonstrated to control microfluidic dynamics due to the enhanced and confined light absorption from…

Optics · Physics 2023-08-01 Sen Yang , Justus C. Ndukaife

Optical Flow (OF) is the movement pattern of pixels or edges that is caused in a visual scene by the relative motion between an agent and a scene. OF is used in a wide range of computer vision algorithms and robotics applications. While the…

Image and Video Processing · Electrical Eng. & Systems 2023-09-25 Jonas Kühne , Michele Magno , Luca Benini

The scarcity of ground-truth labels poses one major challenge in developing optical flow estimation models that are both generalizable and robust. While current methods rely on data augmentation, they have yet to fully exploit the rich…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Jisoo Jeong , Hong Cai , Risheek Garrepalli , Jamie Menjay Lin , Munawar Hayat , Fatih Porikli

Understanding light-matter interaction enables harnessing physical effects to translate into new capabilities realized in modern integrated photonics platforms. Here, we present the design and characterization of optofluidic components in…

Optics · Physics 2022-07-29 Chengkuan Gao , Prabhav Gaur , Shimon Rubin , Yeshaiahu Fainman

Inferring dynamical models from data continues to be a significant challenge in computational biology, especially given the stochastic nature of many biological processes. We explore a common scenario in omics, where statistically…

Machine Learning · Computer Science 2025-07-31 Suryanarayana Maddu , Victor Chardès , Michael. J. Shelley

Fine-grained control of text-to-image diffusion transformer models (DiT) remains a critical challenge for practical deployment. While recent advances such as OminiControl and others have enabled a controllable generation of diverse control…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zhenxiong Tan , Qiaochu Xue , Xingyi Yang , Songhua Liu , Xinchao Wang

Surgical instrument segmentation in laparoscopy is essential for computer-assisted surgical systems. Despite the Deep Learning progress in recent years, the dynamic setting of laparoscopic surgery still presents challenges for precise…

Single particle catalysis aims at determining factors that dictate nanoparticle activity and selectivity. Existing methods often use fluorescent model reactions at low reactant concentrations, operate at low pressures, or rely on plasmonic…

Opto-mechano-fluidic resonators (OMFRs) are a unique optofluidics platform that can measure the acoustic properties of fluids and bioanalytes in a fully-contained microfluidic system. By confining light in ultra-high-Q whispering gallery…

Optics · Physics 2014-05-22 Kaiyuan Zhu , Kewen Han , Tal Carmon , Xudong Fan , Gaurav Bahl

Real-time high-accuracy optical flow estimation is critical for a variety of real-world robotic applications. However, current learning-based methods often struggle to balance accuracy and computational efficiency: methods that achieve high…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Zhiyong Zhang , Aniket Gupta , Huaizu Jiang , Hanumant Singh

Modern optical flow methods make use of salient scene feature points detected and matched within the scene as a basis for sparse-to-dense optical flow estimation. Current feature detectors however either give sparse, non uniform point…

Computer Vision and Pattern Recognition · Computer Science 2019-05-21 Felix Stephenson , Toby Breckon , Ioannis Katramados
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