High-resolution LCOS microdisplay with sub-kHz frame rate for high performance, high precision 3D sensor

Author(s):  
Grigory Lazarev ◽  
Stefanie Bonifer ◽  
Philip Engel ◽  
Daniel Höhne ◽  
Gunther Notni
Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2671 ◽  
Author(s):  
Chunsheng Liu ◽  
Yu Guo ◽  
Shuang Li ◽  
Faliang Chang

You Only Look Once (YOLO) deep network can detect objects quickly with high precision and has been successfully applied in many detection problems. The main shortcoming of YOLO network is that YOLO network usually cannot achieve high precision when dealing with small-size object detection in high resolution images. To overcome this problem, we propose an effective region proposal extraction method for YOLO network to constitute an entire detection structure named ACF-PR-YOLO, and take the cyclist detection problem to show our methods. Instead of directly using the generated region proposals for classification or regression like most region proposal methods do, we generate large-size potential regions containing objects for the following deep network. The proposed ACF-PR-YOLO structure includes three main parts. Firstly, a region proposal extraction method based on aggregated channel feature (ACF) is proposed, called ACF based region proposal (ACF-PR) method. In ACF-PR, ACF is firstly utilized to fast extract candidates and then a bounding boxes merging and extending method is designed to merge the bounding boxes into correct region proposals for the following YOLO net. Secondly, we design suitable YOLO net for fine detection in the region proposals generated by ACF-PR. Lastly, we design a post-processing step, in which the results of YOLO net are mapped into the original image outputting the detection and localization results. Experiments performed on the Tsinghua-Daimler Cyclist Benchmark with high resolution images and complex scenes show that the proposed method outperforms the other tested representative detection methods in average precision, and that it outperforms YOLOv3 by 13.69 % average precision and outperforms SSD by 25.27 % average precision.


Author(s):  
K. Ogura ◽  
H. Nishioka ◽  
N. Ikeo ◽  
T. Kanazawa ◽  
J. Teshima

Structural appraisal of thin film magnetic media is very important because their magnetic characters such as magnetic hysteresis and recording behaviors are drastically altered by the grain structure of the film. However, in general, the surface of thin film magnetic media of magnetic recording disk which is process completed is protected by several-nm thick sputtered carbon. Therefore, high-resolution observation of a cross-sectional plane of a disk is strongly required to see the fine structure of the thin film magnetic media. Additionally, observation of the top protection film is also very important in this field.Recently, several different process-completed magnetic disks were examined with a UHR-SEM, the JEOL JSM 890, which consisted of a field emission gun and a high-performance immerse lens. The disks were cut into approximately 10-mm squares, the bottom of these pieces were carved into more than half of the total thickness of the disks, and they were bent. There were many cracks on the bent disks. When these disks were observed with the UHR-SEM, it was very difficult to observe the fine structure of thin film magnetic media which appeared on the cracks, because of a very heavy contamination on the observing area.


2020 ◽  
Vol 21 ◽  
Author(s):  
Zedong Xiang ◽  
Shaoping Wang ◽  
Haoran Li ◽  
Pingping Dong ◽  
Fan Dong ◽  
...  

Background:: Catalpol, an iridoid glycoside, is one of the richest bioactive components present in Rehmannia glutinosa. More and more metabolites of drugs have exhibit various pharmacological effects, thus providing guidance for clinical application. However, few researches have paid attention on the metabolism of catalpol. Objective:: This study aimed to establish a rapid and effective method to identify catalpol metabolites and evaluate the biotransformation pathways of catalpol in rats. Methods:: In this study, catalpol metabolites in rat urine, plasma and faeces were analyzed by UHPLC-Q-Exactive MS for the characterization of metabolism of catalpol. Based on high-resolution extracted ion chromatograms (HREICs) and parallel reaction monitoring mode (PRM), metabolites of catalpol were identified by comparing the diagnostic product ions (DPIs), chromatographic retention times, neutral loss fragments (NLFs) and accurate mass measurement with those of catalpol reference standard. Results: A total of 29 catalpol metabolites were detected and identified in both negative and positive ion modes. Nine metabolic reactions including deglycosylation, hydroxylation, dihydroxylation, hydrogenation, dehydrogenation, oxidation of methylene to ketone, glucuronidation, glycine conjugation and cysteine conjugation were proposed. Conclusion:: A rapid and effective method based on UHPLC-Q-Exactive MS was developed to mine the metabolism information of catalpol. Results of metabolites and biotransformation pathways of catalpol suggested that when orally administrated, catalpol was firstly metabolized into catalpol aglycone, after which phase Ⅰ and phase Ⅱ reactions occurred. However, hydrophilic chromatography-mass spectrometry still needed to further find the polar metabolites of catalpol.


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