scholarly journals Image-free classification of fast-moving objects using “learned” structured illumination and single-pixel detection

2020 ◽  
Vol 28 (9) ◽  
pp. 13269 ◽  
Author(s):  
Zibang Zhang ◽  
Xiang Li ◽  
Shujun Zheng ◽  
Manhong Yao ◽  
Guoan Zheng ◽  
...  
Keyword(s):  
Fast Moving ◽  
Moving Objects ◽  
Structured Illumination ◽  
Free Classification ◽  
Single Pixel

scholarly journals Towards automated cancer screening: Label-free classification of fixed cell samples using wavelength modulated Raman spectroscopy

2018 ◽  
Vol 11 (4) ◽  
pp. e201700244 ◽  
Author(s):  
Lana Woolford ◽  
Mingzhou Chen ◽  
Kishan Dholakia ◽  
C. Simon Herrington
Keyword(s):  
Raman Spectroscopy ◽  
Cancer Screening ◽  
Label Free ◽  
Fixed Cell ◽  
Free Classification

Towards parameter-free classification of sound effects in movies

2005 ◽  
Author(s):  
Selina Chu ◽  
Shrikanth Narayanan ◽  
C.-C. J. Kuo
Keyword(s):  
Sound Effects ◽  
Free Classification

Robust Autonomous Car-Like Robot Tracking Based on Tracking-Learning-Detection

2014 ◽  
Vol 687-691 ◽  
pp. 564-571 ◽  
Author(s):  
Lin Bao Xu ◽  
Shu Ming Tang ◽  
Jin Feng Yang ◽  
Yan Min Dong
Keyword(s):  
Optical Flow ◽  
Fast Moving ◽  
Moving Objects ◽  
Tracking Algorithm ◽  
Robust Tracking ◽  
Symmetry Detection ◽  
Tracking Method ◽  
Robot Tracking ◽  
Improve Accuracy ◽  
First Time

This paper proposes a robust tracking algorithm for an autonomous car-like robot, and this algorithm is based on the Tracking-Learning-Detection (TLD). In this paper, the TLD method is extended to track the autonomous car-like robot for the first time. In order to improve accuracy and robustness of the proposed algorithm, a method of symmetry detection of autonomous car-like robot rear is integrated into the TLD. Moreover, the Median-Flow tracker in TLD is improved with a pyramid-based optical flow tracking method to capture fast moving objects. Extensive experiments and comparisons show the robustness of the proposed method.

Classification of moving objects in atmospherically degraded video

2012 ◽  
Vol 51 (10) ◽  
pp. 1 ◽  
Author(s):  
Eli Chen ◽  
Oren Haik ◽  
Yitzhak Yitzhaky
Keyword(s):  
Moving Objects

scholarly journals Answers to Fundamental Questions in Superresolution Microscopy

2021 ◽  
Author(s):  
Rainer Heintzmann
Keyword(s):  
Light Microscopy ◽  
Prior Knowledge ◽  
Near Field ◽  
Structured Illumination ◽  
Resolution Limit ◽  
Structured Illumination Microscopy ◽  
Technical Aspects ◽  
Superresolution Microscopy ◽  
Definition Of

This article presents answers to the questions on superresolution and structured illumination microscopy as raised in the editorial of a recent publication [K. Prakash et al. arXiv, 2102.13649, 2021]. The answers are based on my personal views on superresolution in light microscopy, supported by reasoning. Discussed are the definition of superresolution, Abbe’s resolution limit and the classification of superresolution methods into non-linear-, prior-knowledge- and near-field-based superresolution. A further focus is put on capabilities and technical aspects of present and future structured illumination microscopy (SIM) methods.

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