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Record 121 of
Title:A star identification algorithm based on radial and dynamic cyclic features of star pattern
Author(s):Wei, Xin(1,2); Wen, Desheng(1); Song, Zongxi(1); Xi, Jiangbo(3); Zhang, Weikang(1,2); Liu, Gang(1,2); Li, Zhixin(1,2)
Source: Advances in Space Research Volume: 63 Issue: 7 DOI: 10.1016/j.asr.2018.12.027 Published: 1 April 2019
Abstract:A full-sky star identification algorithm based on radial and dynamic cyclic patterns is presented with the aim of solving the "lost-in-space" problem. The dynamic cyclic pattern match is applied with a maximum cumulate comparison method to identify sensor-catalog pairings in initial match, which substantially eliminates the effects of the star position noise, magnitude noise, and false stars. After initial match pairings of stars are obtained, a chain part extension technique is employed to quickly search for the longest match chain as the final result. Experimental results indicate that the proposed algorithm is highly robust to star position noise, magnitude noise and false stars. In a series of simulations, the identification rate of the algorithm is 97.50% with 2.0 pixels star position noise, 96.90% with 0.4 Mv star magnitude noise and 95.30% with four false stars respectively. Moreover, the algorithm achieves an identification rate of 58.08% when only six stars are in the field of view. ? 2018 COSPAR
Accession Number: 20190206361056
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Record 122 of
Title:A scanning-free wide-field single-fiber endoscopic image retrieval method based on optical transmission matrix
Author(s):Xu, Chengfang(1,2,3); Zhuang, Bin(1,3); Geng, Yi(1,3); Chen, Hui(1,3); Ren, Liyong(1); Wu, Zhaoxin(2)
Source: Laser Physics Volume: 29 Issue: 4 DOI: 10.1088/1555-6611/ab0365 Published: March 6, 2019
Abstract:Light waves transmitting in a multimode optical fiber (MMF) for endoscopic imaging, due to modal dispersion, inevitably suffer two severe distortions: on the way in for illuminating and on the way out for imaging, which becomes a big challenge when using a single MMF for endoscopic applications. In this paper, based on obtaining the optical transmission matrix of the MMF working in the endoscopic mode, we propose a new method for retrieving endoscopic images from speckle fields, where the two distortions could be eliminated simultaneously. Our experimental results demonstrate that the object images can be well reconstructed directly from distorted waves. In addition, no scanning operation is required when collecting images, which is timesaving. Such an efficient method might have potential applications for wide-field and ultrathin fiber endoscopic imaging. ? 2019 Astro Ltd.
Accession Number: 20191806859871
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Record 123 of
Title:Bidirectional adaptive feature fusion for remote sensing scene classification
Author(s):Lu, Xiaoqiang(1); Ji, Weijun(1,2); Li, Xuelong(1,2); Zheng, Xiangtao(1)
Source: Neurocomputing Volume: 328 Issue: DOI: 10.1016/j.neucom.2018.03.076 Published: 7 February 2019
Abstract:Scene classification has become an effective way to interpret the High Spatial Resolution (HSR) remote sensing images. Recently, Convolutional Neural Networks (CNN) have been found to be excellent for scene classification. However, only using the deep models as feature extractor on the aerial image directly is not proper, because the extracted deep features can not capture spatial scale variability and rotation variability in HSR remote sensing images. To relieve this limitation, a bidirectional adaptive feature fusion strategy is investigated to deal with the remote sensing scene classification. The deep learning feature and the SIFT feature are fused together to get a discriminative image presentation. The fused feature can not only describe the scenes effectively by employing deep learning feature but also overcome the scale and rotation variability with the usage of the SIFT feature. By fusing both SIFT feature and global CNN feature, our method achieves state-of-the-art scene classification performances on the UCMerced, the Sydney and the AID datasets. ? 2018 Elsevier B.V.
Accession Number: 20184105928060
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Record 124 of
Title:Numerical study and test of the APS linac transverse deflecting cavity
Author(s):Hui, D.(1,2,3); Sun, Y.(1); Smith, T.(1); Luo, D.(1,2,3); Yao, C.-Y.(1); Tian, J.(2)
Source: Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment Volume: 923 Issue: DOI: 10.1016/j.nima.2019.01.043 Published: 11 April 2019
Abstract:The transverse deflecting cavity can be used to transform particle distributions in the 6D phase space, which makes it a promising component in phase space beam diagnostics and beam manipulations. In the Advanced Photon Source (APS) Linac, a LOLA-type traveling wave deflecting cavity was installed for the diagnostics of beam characteristics, such as the bunch length, bunch temporal profile, time-dependent energy spread and slice (time-correlated) transverse emittance. In this paper, this deflecting cavity is modeled and analyzed with the numerical method. The effects of the center cell and coupler cell dimensions on the performance of the whole structure are studied, which shows the coupler cell radius has a dominant effect over the coupler cell length and slot width on the global reflection coefficient and field flatness. Important RF parameters, such as S11, field flatness and phase advance etc., of the LOLA-II cavity in tuning are calculated and discussed. After optimization, the field flatness of the cavity is 2.1%, the phase advance is 119.66° degrees with a standard deviation smaller than 0.5° and the bandwidth is 15.738 MHz when VSWR 11 ? 2019
Accession Number: 20190606474785
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Record 125 of
Title:Detection of ships in inland river using high-resolution optical satellite imagery based on mixture of deformable part models
Author(s):Song, Pengfei(1,2,3); Qi, Lei(1,4); Qian, Xueming(2); Lu, Xiaoqiang(1)
Source: Journal of Parallel and Distributed Computing Volume: 132 Issue: DOI: 10.1016/j.jpdc.2019.04.013 Published: October 2019
Abstract:Ship detection using optical satellite imagery is of great significance in many applications such as traffic surveillance, pollution monitoring, etc. So far, a lot of ship detection methods have been developed for images covering open sea, offshore area and harbors. Compared to the ship detection in sea and offshore area, it is more difficult to detect ships in inland river due to several challenges. First of all, many ships in inland river are clustered together and hard to be separated from each other. Secondly, ships lying alongside the pier are very likely to be recognized as part of the pier. Thirdly, ships in inland river is usually smaller than those in the sea. A hierarchical method is proposed to detect the ships in inland river in this paper. The Regions of Interest (ROIs) are firstly extracted based on water–land segmentation using multi-spectral information. Then two kinds of ship candidates are extracted based on the panchromatic band. The isolated ships are detected by analyzing the shape of connected components and the clustered ships are detected by using mixtures multi-scale Deformable Part Models (DPM) and Histogram of Oriented Gradient (HOG). At last, a Back Propagation Neural Network (BPNN) is trained to classify the ship candidates using the multi-spectral bands. The experiments using Quickbird satellite images show that our approach is effective in ship detection and performs particularly well in separating the ships clustered together and staying alongside the pier. ? 2019 Elsevier Inc.
Accession Number: 20192307001867
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Record 126 of
Title:Deep binary reconstruction for cross-modal hashing
Author(s):Hu, Di(1); Nie, Feiping(1); Li, Xuelong(2,3)
Source: IEEE Transactions on Multimedia Volume: 21 Issue: 4 DOI: 10.1109/TMM.2018.2866771 Published: April 2019
Abstract:To satisfy the huge storage space and organization capacity requirements in addressing big multimodal data, hashing techniques have been widely employed to learn binary representations in cross-modal retrieval tasks. However, optimizing the hashing objective under the necessary binary constraint is truly a difficult problem. A common strategy is to relax the constraint and perform individual binarizations over the learned real-valued representations. In this paper, in contrast to conventional two-stage methods, we propose to directly learn the binary codes, where the model can be easily optimized by a standard gradient descent optimizer. However, before that, we present a theoretical guarantee of the effectiveness of the multimodal network in preserving the inter-and intra-modal consistencies. Based on this guarantee, a novel multimodal deep binary reconstruction model is proposed, which can be trained to simultaneously model the correlation across modalities and learn the binary hashing codes. To generate binary codes and to avoid the tiny gradient problem, a novel activation function first scales the input activations to suitable scopes and, then, feeds them to the tanh function to build the hashing layer. Such a composite function is named adaptive tanh. Both linear and nonlinear scaling methods are proposed and shown to generate efficient codes after training the network. Extensive ablation studies and comparison experiments are conducted for the image2text and text2image retrieval tasks; the method is found to outperform several state-of-The-Art deep-learning methods with respect to different evaluation metrics. ? 1999-2012 IEEE.
Accession Number: 20183605786074
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Record 127 of
Title:Weather recognition via classification labels and weather-cue maps
Author(s):Zhao, Bin(1); Hua, Lulu(1); Li, Xuelong(1); Lu, Xiaoqiang(2); Wang, Zhigang(1)
Source: Pattern Recognition Volume: 95 Issue: DOI: 10.1016/j.patcog.2019.06.017 Published: November 2019
Abstract:Although it is of great importance to recognize weather conditions automatically, this task has not been explored thoroughly in practice. Generally, most approaches in the literature simply treat it as a common image classification task, i.e., assigning a certain weather label to each image. However, there are significant differences between weather recognition and common image classification, since several weather conditions tend to occur simultaneously, like foggy and cloudy. Obviously, a single weather label is insufficient to provide a comprehensive description of the weather conditions. In this case, we propose to utilize auxiliary weather-cues, e.g., black clouds and blue sky, for comprehensive weather description. Specifically, a multi-task framework is designed to jointly deal with the weather-cue segmentation task and weather classification task. Benefit from the intrinsic relationships lying in the two tasks, exploring the information of weather-cues can not only provide a comprehensive description of weather conditions, but also help the weather classification task to learn more effective features, and further improve the performance. Besides, we construct two large-scale weather recognition datasets equipped with both weather labels and segmentation masks of weather-cues. Experiment results demonstrate the excellent performance of our approach. The constructed two datasets will be available at https://github.com/wzgwzg/Multitask_Weather. ? 2019 Elsevier Ltd
Accession Number: 20192707146229
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Record 128 of
Title:Electron-transfer cascade from CdSe@ZnSe core-shell quantum dot accelerates photoelectrochemical H2 evolution on TiO2 nanotube arrays
Author(s):Jia, Jia(1); Xue, Peng(1); Hu, Xiaoyun(2); Wang, Yishan(3); Liu, Enzhou(1,2); Fan, Jun(1)
Source: Journal of Catalysis Volume: 375 Issue: DOI: 10.1016/j.jcat.2019.05.028 Published: July 2019
Abstract:A novel TiO2-CdSe-ZnSe electron-transfer cascade heterostructure with nanoscale precision is synthesized for hydrogen evolution, exhibiting an obvious hierarchical absorption and improved separation efficiency for photocarriers. The key to this constructed structure lies in the in-situ deposition of CdSe quantum-dots onto the surface of TiO2 followed by the epitaxial growth of a ZnSe shell. In this conditions, the CdSe core can serve as a buffer layer for the electrons on the conduction band of the ZnSe shell, enabling them to rapidly migrate to the TiO2 and later to the opposite electrode to produce H2; meanwhile, due to high injection efficiency in the cascade type II structure, holes from TiO2 are transferred to the electrolyte interface, where the oxidation reaction of hole trapping scavenger occurs. Surprisingly, this heterostructure shows a significantly enhanced photocurrent density (1.45 mA cm?2), favorable H2 production rates (252 μmol h?1 cm?2) and moderate durability under light irradiation. ? 2019 Elsevier Inc.
Accession Number: 20192407025900
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Record 129 of
Title:Image information from a dual channel optical synthetic aperture imaging system
Author(s):Chen, Liwu(1,2); Zhao, Boacheng(4); Chen, Ren(1,2); Gao, Cong(1,2,3)
Source: Proceedings of SPIE - The International Society for Optical Engineering Volume: 11023 Issue: DOI: 10.1117/12.2522481 Published: 2019
Abstract:Introduce an optic system which by two fields of the system to observe the same object, it acquire two channels image of the object on the first imaging plate; and one by one the two channels image collimated by the array lens after them, then all the collimated beams were collected into the second image plate. As the two channels image were focus into the second image plate, super-resolution image of the object were acquired. The photos of the experiment proved this. ? 2019 SPIE.
Accession Number: 20191506748649
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Record 130 of
Title:Map detection of probabilistically shaped constellations in optical fiber transmissions
Author(s):Hu, Shaohua(1); Zhang, Wenjing(1); Yi, Xingwen(2,3); Li, Zhaohui(2,3); Li, Fan(2,3); Huang, Xinning(3); Zhu, Mingyue(1); Jingzhang(1); Qiu, Kun(1)
Source: Optics InfoBase Conference Papers Volume: Part F160-OFC 2019 Issue: DOI: null Published: 2019
Abstract:We present the theoretical analysis and experimental demonstration of MAP detection that outperforms the conventional detection for probabilistically shaped constellations in optical fiber transmissions. Larger BER improvements are observed for the stronger shaped constellations. ? OSA 2019 ? 2019 The Author(s)
Accession Number: 20202208771950
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Record 131 of
Title:Quantitative phase imaging of cells in a flow cytometry arrangement utilizing Michelson interferometer-based off-axis digital holographic microscopy
Author(s):Min, Junwei(1,2); Yao, Baoli(2); Trendafilova, Veselina(1); Ketelhut, Steffi(1); Kastl, Lena(1); Greve, Burkhard(3); Kemper, Bj?rn(1)
Source: Journal of Biophotonics Volume: 12 Issue: 9 DOI: 10.1002/jbio.201900085 Published: September 1, 2019
Abstract:We combined Michelson-interferometer-based off-axis digital holographic microscopy (DHM) with a common flow cytometry (FCM) arrangement. Utilizing object recognition procedures and holographic autofocusing during the numerical reconstruction of the acquired off-axis holograms, sharply focused quantitative phase images of suspended cells in flow were retrieved without labeling, from which biophysical cellular features of distinct cells, such as cell radius, refractive index and dry mass, can be subsequently retrieved in an automated manner. The performance of the proposed concept was first characterized by investigations on microspheres that were utilized as test standards. Then, we analyzed two types of pancreatic tumor cells with different morphology to further verify the applicability of the proposed method for quantitative live cell imaging. The retrieved biophysical datasets from cells in flow are found in good agreement with results from comparative investigations with previously developed DHM methods under static conditions, which demonstrates the effectiveness and reliability of our approach. Our results contribute to the establishment of DHM in imaging FCM and prospect to broaden the application spectrum of FCM by providing complementary quantitative imaging as well as additional biophysical cell parameters which are not accessible in current high-throughput FCM measurements. ? 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Accession Number: 20192607106774
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Record 132 of
Title:Microwave and RF Photonic Fractional Hilbert Transformer Based on a 50 GHz Kerr Micro-Comb
Author(s):Tan, Mengxi(1); Mitchell, Arnan(2); Moss, David J.(1); Xu, Xingyuan(1); Corcoran, Bill(3); Wu, Jiayang(1); Boes, Andreas(2); Nguyen, Thach G.(2); Chu, Sai T.(4); Little, Brent E.(5); Morandotti, Roberto(6,7,8)
Source: Journal of Lightwave Technology Volume: 37 Issue: 24 DOI: 10.1109/JLT.2019.2946606 Published: December 15, 2019
Abstract:We report a photonic microwave and radio frequency (RF) fractional Hilbert transformer based on an integrated Kerr micro-comb source. The micro-comb source has a free spectral range (FSR) of 50 GHz, generating a large number of comb lines that serve as a high-performance multi-wavelength source for the transformer. By programming and shaping the comb lines according to calculated tap weights, we achieve both arbitrary fractional orders and a broad operation bandwidth. We experimentally characterize the RF amplitude and phase response for different fractional orders and perform system demonstrations of real-time fractional Hilbert transforms. We achieve a phase ripple of ? 1983-2012 IEEE.
Accession Number: 20195307946734
