A high-precision range extraction method using an FM nonlinear kernel function for DFB-array-based FMCW lidar

2022 ◽  
Vol 504 ◽  
pp. 127469
Author(s):  
Cheng Lu ◽  
Zehao Yu ◽  
Guodong Liu
Keyword(s):  
High Precision ◽  
Kernel Function ◽  
Extraction Method

scholarly journals ACF Based Region Proposal Extraction for YOLOv3 Network Towards High-Performance Cyclist Detection in High Resolution Images

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2671 ◽  
Author(s):  
Chunsheng Liu ◽  
Yu Guo ◽  
Shuang Li ◽  
Faliang Chang
Keyword(s):  
High Resolution ◽  
High Precision ◽  
Extraction Method ◽  
High Performance ◽  
Detection Methods ◽  
Average Precision ◽  
Deep Network ◽  
High Resolution Images ◽  
Bounding Boxes ◽  
Detection And Localization

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.

Image Edge Extraction Based on SUSAN Operator

2014 ◽  
Vol 687-691 ◽  
pp. 3765-3768
Author(s):  
Nan Wang
Keyword(s):  
Edge Detection ◽  
High Precision ◽  
Extraction Method ◽  
The Other ◽  
Differential Detection ◽  
Edge Extraction ◽  
Image Edge ◽  
Circular Template

A new edge extraction method was put forward based on the SUSAN operator, according to the problems of poor anti-noise ability and edge detection incomplete of the conventional differential detection operator. The circular template and the center of the circle (template nuclear) were used in this method, the numbers of pixels was calculated through the comparison pixels value of template with the other points of pixels in the template circle, and then compared with the threshold, so as to the edge of images was extracted. The results showed that this method had high precision, and could be able to fully extract the edge of images. It is an effective method of extracting the edge of images.

Rapid determination of Ba isotope compositions for barites using a H2O-extraction method and MC-ICP-MS

2020 ◽  
Vol 35 (8) ◽  
pp. 1566-1573
Author(s):  
Lan-Lan Tian ◽  
Ying-Zeng Gong ◽  
Wei Wei ◽  
Jin-Ting Kang ◽  
Hui-Min Yu ◽  
...  
Keyword(s):  
High Precision ◽  
Extraction Method ◽  
Rapid Determination ◽  
Simple Method ◽  
Icp Ms ◽  
Isotope Measurement

This study presents a rapid and simple method of high precision Ba isotope measurement for barite using H2O extraction.

Uniform distributed subpixel ORB feature extraction method for high-precision SLAM

2018 ◽  
Vol 26 (10) ◽  
pp. 2575-2583 ◽  
Author(s):  
张 一 ZHANG Yi ◽  
姜 挺 JIANG Ting ◽  
江刚武 JIANG Gang-wu ◽  
于 英 YU Ying ◽  
周 远 ZHOU Yuan
Keyword(s):  
Feature Extraction ◽  
High Precision ◽  
Extraction Method ◽  
Feature Extraction Method

Comparison of F o Extraction Methods for High-Precision Voice Perturbation Measurements

1993 ◽  
Vol 36 (6) ◽  
pp. 1120-1133 ◽  
Author(s):  
Ingo R. Titze ◽  
Haixiang Liang
Keyword(s):  
High Precision ◽  
Amplitude Modulation ◽  
Extraction Method ◽  
Signal To Noise Ratio ◽  
Extraction Methods ◽  
Sampling Frequency ◽  
Peak Picking ◽  
Signal To Noise ◽  
Zero Crossing ◽  
Software Implementations

Voice perturbation measures, such as jitter and shimmer, depend on accurate extraction of fundamental frequency (F o ) and amplitude of various waveform types. The extraction method directly affects the accuracy of the measures, particularly if several waveform types (with or without formant structure) are under consideration and if noise and modulation are present in the signal. For frequency perturbation, high precision is defined here as the ability to extract F o to ±0.01% under conditions of noise and modulation. Three F o -extraction methods and their software implementations are discussed and compared. The methods are cycle-to-cycle waveform matching, zero-crossing and peak-picking. Interpolation between samples is added to make the extractions more accurate and reliable. The sensitivity of the methods to different parameters such as sampling frequency, mean F o , signal-to-noise ratio, frequency modulation, and amplitude modulation are explored.

scholarly journals An Enhancement Deep Feature Extraction Method for Bearing Fault Diagnosis Based on Kernel Function and Autoencoder

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Fengtao Wang ◽  
Bosen Dun ◽  
Xiaofei Liu ◽  
Yuhang Xue ◽  
Hongkun Li ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Fault Diagnosis ◽  
Kernel Function ◽  
Extraction Method ◽  
Operating Conditions ◽  
Model Parameters ◽  
Layer By Layer ◽  
Feature Extraction Method ◽  
Deep Feature ◽  
Deep Feature Extraction

Rotating machinery vibration signals are nonstationary and nonlinear under complicated operating conditions. It is meaningful to extract optimal features from raw signal and provide accurate fault diagnosis results. In order to resolve the nonlinear problem, an enhancement deep feature extraction method based on Gaussian radial basis kernel function and autoencoder (AE) is proposed. Firstly, kernel function is employed to enhance the feature learning capability, and a new AE is designed termed kernel AE (KAE). Subsequently, a deep neural network is constructed with one KAE and multiple AEs to extract inherent features layer by layer. Finally, softmax is adopted as the classifier to accurately identify different bearing faults, and error backpropagation algorithm is used to fine-tune the model parameters. Aircraft engine intershaft bearing vibration data are used to verify the method. The results confirm that the proposed method has a better feature extraction capability, requires fewer iterations, and has a higher accuracy than standard methods using a stacked AE.

scholarly journals Systematic and Statistical Uncertainties of the Hilbert-Transform Based High-precision FID Frequency Extraction Method

2021 ◽  
pp. 107020
Author(s):  
Ran Hong ◽  
Simon Corrodi ◽  
Saskia Charity ◽  
Stefan Baeßler ◽  
Jason Bono ◽  
...  
Keyword(s):  
High Precision ◽  
Hilbert Transform ◽  
Extraction Method ◽  
The Hilbert Transform

Evaluation of the dark field method for large association of spread DNA

1978 ◽  
Vol 36 (2) ◽  
pp. 190-191
Author(s):  
Douglas C. Barker
Keyword(s):  
Electron Microscopy ◽  
Molecular Weight ◽  
Mitochondrial Dna ◽  
Extraction Method ◽  
Field Method ◽  
Dark Field ◽  
Kinetoplast Dna ◽  
Field Electron ◽  
Field Electron Microscopy ◽  
Dark Field Electron

A number of satisfactory methods are available for the electron microscopy of nicleic acids. These methods concentrated on fragments of nuclear, viral and mitochondrial DNA less than 50 megadaltons, on denaturation and heteroduplex mapping (Davies et al 1971) or on the interaction between proteins and DNA (Brack and Delain 1975). Less attention has been paid to the experimental criteria necessary for spreading and visualisation by dark field electron microscopy of large intact issociations of DNA. This communication will report on those criteria in relation to the ultrastructure of the (approx. 1 x 10-14g) DNA component of the kinetoplast from Trypanosomes. An extraction method has been developed to eliminate native endonucleases and nuclear contamination and to isolate the kinetoplast DNA (KDNA) as a compact network of high molecular weight. In collaboration with Dr. Ch. Brack (Basel [nstitute of Immunology), we studied the conditions necessary to prepare this KDNA Tor dark field electron microscopy using the microdrop spreading technique.

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