2016

• Record 397 of
  
  Title:Aging Face Recognition: A Hierarchical Learning Model Based on Local Patterns Selection
  
  Author(s):Li, Zhifeng(1); Gong, Dihong(1); Li, Xuelong(2); Tao, Dacheng(3)
  Source: IEEE Transactions on Image Processing  Volume: 25  Issue: 5  DOI: 10.1109/TIP.2016.2535284  Published: May 2016  
  Abstract:Aging face recognition refers to matching the same person's faces across different ages, e.g., matching a person's older face to his (or her) younger one, which has many important practical applications, such as finding missing children. The major challenge of this task is that facial appearance is subject to significant change during the aging process. In this paper, we propose to solve the problem with a hierarchical model based on two-level learning. At the first level, effective features are learned from low-level microstructures, based on our new feature descriptor called local pattern selection (LPS). The proposed LPS descriptor greedily selects low-level discriminant patterns in a way, such that intra-user dissimilarity is minimized. At the second level, higher level visual information is further refined based on the output from the first level. To evaluate the performance of our new method, we conduct extensive experiments on the MORPH data set (the largest face aging data set available in the public domain), which show a significant improvement in accuracy over the state-of-the-art methods. © 2015 IEEE.
  Accession Number: 20161702294167
• Record 398 of
  
  Title:Deep semantic understanding of high resolution remote sensing image
  
  Author(s):Qu, Bo(1,2); Li, Xuelong(1); Tao, Dacheng(3); Lu, Xiaoqiang(1)
  Source: IEEE CITS 2016 - 2016 International Conference on Computer, Information and Telecommunication Systems  Volume:   Issue:   DOI: 10.1109/CITS.2016.7546397  Published: August 16, 2016  
  Abstract:With the rapid development of remote sensing technology, huge quantities of high resolution remote sensing images are available now. Understanding these images in semantic level is of great significance. Hence, a deep multimodal neural network model for semantic understanding of the high resolution remote sensing images is proposed in this paper, which uses both visual and textual information of the high resolution remote sensing images to generate natural sentences describing the given images. In the proposed model, the convolution neural network is utilized to extract the image feature, which is then combined with the text descriptions of the images by RNN or LSTMs. And in the experiments, two new remote sensing image-captions datasets are built at first. Then different kinds of CNNs with RNN or LSTMs are combined to find which is the best combination for caption generation. The experiments results prove that the proposed method achieves good performances in semantic understanding of high resolution remote sensing images. © 2016 IEEE.
  Accession Number: 20163802815457
• Record 399 of
  
  Title:Space debris detection in optical image sequences
  
  Author(s):Xi, Jiangbo(1,2,3); Wen, Desheng(1); Ersoy, Okan K.(3); Yi, Hongwei(1); Yao, Dalei(1); Song, Zongxi(1); Xi, Shaobo(4)
  Source: Applied Optics  Volume: 55  Issue: 28  DOI: 10.1364/AO.55.007929  Published: October 1, 2016  
  Abstract:We present a high-accuracy, low false-alarm rate, and low computational-cost methodology for removing stars and noise and detecting space debris with low signal-to-noise ratio (SNR) in optical image sequences. First, time-index filtering and bright star intensity enhancement are implemented to remove stars and noise effectively. Then, a multistage quasi-hypothesis-testing method is proposed to detect the pieces of space debris with continuous and discontinuous trajectories. For this purpose, a time-index image is defined and generated. Experimental results show that the proposed method can detect space debris effectively without any false alarms. When the SNR is higher than or equal to 1.5, the detection probability can reach 100%, and when the SNR is as low as 1.3, 1.2, and 1, it can still achieve 99%, 97%, and 85% detection probabilities, respectively. Additionally, two large sets of image sequences are tested to show that the proposed method performs stably and effectively. © 2016 Optical Society of America.
  Accession Number: 20164102879718
• Record 400 of
  
  Title:Semantic photo retargeting under noisy image labels
  
  Author(s):Zhang, Luming(1); Li, Xuelong(2); Nie, Liqiang(3); Yan, Yan(4); Zimmermann, Roger(3)
  Source: ACM Transactions on Multimedia Computing, Communications and Applications  Volume: 12  Issue: 3  DOI: 10.1145/2886775  Published: May 2016  
  Abstract:With the popularity of mobile devices, photo retargeting has become a useful technique that adapts a high-resolution photo onto a low-resolution screen. Conventional approaches are limited in two aspects. The first factor is the de-emphasized role of semantic content that is many times more important than lowlevel features in photo aesthetics. Second is the importance of image spatial modeling: Toward a semantically reasonable retargeted photo, the spatial distribution of objects within an image should be accurately learned. To solve these two problems, we propose a new semantically aware photo retargeting that shrinks a photo according to region semantics. The key technique is a mechanism transferring semantics of noisy image labels (inaccurate labels predicted by a learner like an SVM) into different image regions. In particular, we first project the local aesthetic features (graphlets in this work) onto a semantic space, wherein image labels are selectively encoded according to their noise level. Then, a category-sharing model is proposed to robustly discover the semantics of each image region. The model is motivated by the observation that the semantic distribution of graphlets from images tagged by a common label remains stable in the presence of noisy labels. Thereafter, a spatial pyramid is constructed to hierarchically encode the spatial layout of graphlet semantics. Based on this, a probabilistic model is proposed to enforce the spatial layout of a retargeted photo to be maximally similar to those from the training photos. Experimental results show that (1) noisy image labels predicted by different learners can improve the retargeting performance, according to both qualitative and quantitative analysis, and (2) the category-sharing model stays stable even when 32.36% of image labels are incorrectly predicted. ©2016 ACM.
  Accession Number: 20162302459216
• Record 401 of
  
  Title:Polyfurfuryl alcohol spheres template synthesis of 3D porous graphene for high-performance supercapacitor application
  
  Author(s):Ma, Cunliang(1); Peng, Li(2); Feng, Yafei(1); Shen, Jiaxin(1); Xiao, Zhuangqing(1); Cai, Kaiyu(1); Yu, Youhai(3); Min, Yong(1); Epstein, Arthur J.(4)
  Source: Synthetic Metals  Volume: 220  Issue:   DOI: 10.1016/j.synthmet.2016.06.008  Published: October 1, 2016  
  Abstract:In this work, a 3D porous graphene (3DrGO) was prepared by a hydrothermal assembly process of graphene oxide (GO) using polyfurfuryl alcohol (PFA) spheres as the template followed by thermal reduction. The introduction of PFA spheres can effectively enlarge the interspace between graphene sheets and suppresses their re-stacking in the thermal treatment. The 3DrGO was further composted with PANI nanowire. The structure and the property of 3DrGO and 3DrGO/PANI composite have been characterized by transmission electron microscopy, scanning electron microscopy, X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, X-ray diffraction, cyclic voltammetry, galvanostatic charge-discharge test and electrochemical impedance spectroscopy. Electrochemical test reveals that the 3DrGO has good capacitance performance of 104 F/g at current charge-discharge current density of 1A/g and the capacitance performance increase to 530 F/g after further composed with PANI nanowire. Both 3DrGO and 3DrGO/PANI show excellent capacity retention rates of 95% and 88%, respectively, after 1000 cycles. All these impressive results demonstrate that the material obtained by this approach is greatly promising for application in high-performance supercapacitors. © 2016 Elsevier B.V. All rights reserved.
  Accession Number: 20162702552627
• Record 402 of
  
  Title:Optically bound colloidal lattices in evanescent optical fields
  
  Author(s):Han, Xiang(1,2); Luo, Hui(1); Xiao, Guangzong(1,3); Jones, Philip H.(2)
  Source: Optics Letters  Volume: 41  Issue: 21  DOI: 10.1364/OL.41.004935  Published: November 1, 2016  
  Abstract:In this Letter, we demonstrate the formation of a stable two-dimensional lattice of colloidal particles in the interference pattern formed by four evanescent optical fields at a dielectric interface. The microspheres are observed to form a two-dimensional square lattice with lattice vectors inclined relative to the beam propagation directions. We use digital video microscopy and particle tracking to measure the Brownian motion of particles bound in the lattice, and use this to characterize fluctuations in the local ordering of particles using the bond orientational order parameter, the probability distribution of which is shown to be a chi-squared distribution. An explanation for the form of this distribution is presented in terms of fluctuations of the modes of a ring of particles connected by springs. © 2016 Optical Society of America.
  Accession Number: 20164703034496
• Record 403 of
  
  Title:Analysis of a Si-nanocrystal strip-loaded waveguide for nonlinear applications
  
  Author(s):Wei, Pengjiang(1); Wang, S.H.(2); Little, Brent E.(3); Chu, Sai Tak(1)
  Source: 2016 21st OptoElectronics and Communications Conference, OECC 2016 - Held Jointly with 2016 International Conference on Photonics in Switching, PS 2016  Volume:   Issue:   DOI:   Published: October 26, 2016  
  Abstract:We investigate the nonlinear properties of the doped silica glass integrated waveguide platform with a Si-nc strip-loaded structure. We show the nonlinear properties is drastically enhanced by adding a Si-nc layer in the waveguide core. © 2016 IEICE.
  Accession Number: 20164903083729
• Record 404 of
  
  Title:Navigation and geo-tracking system of UAV EO payload
  
  Author(s):Chen, Ying(1); Zhen, Kang(1); Xue, Yuanyuan(1); Zhang, Xiajiang(1); Li, Yingjuan(1); Tang, Chao(2)
  Source: Proceedings of SPIE - The International Society for Optical Engineering  Volume: 9796  Issue:   DOI: 10.1117/12.2229478  Published: 2016  
  Abstract:A multi-function system based on inertial measurement unit (IMU) is introduced, which can fulfill navigation, attitude measurement of LOS in payload, platform stabilization and tracking control. The IMU is integrated with electro-optical sensors and a laser range finder on gimbals, which performs attitude calculation and navigation by constructing navigation coordinates in a mathematic platform, and the platform navigation information is obtained by transformation matrix between platform and gimbal coordinates. The platform comprising of gyros, electro-optical sensors and servo mechanism is capable of stabilizing line of sight and could be used to geo-tracking in the relevant field of view (FOV).The system can determine geography coordinates of the host platform and target only with navigation information and laser ranging data. The geo-tracking system always locked the target image at the center of FOV by calculating spatial geometry and adjusting LOS attitude. This tracking is different from TV tracking and geographical reference image tracking, which may be influenced by fog and obscurant. When the UAV is flying over urban or mountain areas for rescue missions, it can avoid the loss of targets due to strong maneuver or LOS obscuration, and reduce the operation load and improve rescue efficiency. © 2016 SPIE.
  Accession Number: 20163502747296
• Record 405 of
  
  Title:A parallel alternating direction method with application to compound l1-regularized imaging inverse problems
  
  Author(s):He, Chuan(1); Hu, Changhua(1); Li, Xuelong(2); Yang, Xiaogang(1); Zhang, Wei(1)
  Source: Information Sciences  Volume: 348  Issue:   DOI: 10.1016/j.ins.2016.01.087  Published: June 20, 2016  
  Abstract:We derive a parallel alternating direction method of multipliers (PADMM) and apply it to compound l1-regularized imaging inverse problems. The proposed method is capable of locating the saddle point of large-scale convex minimization problems with the sum of several nonsmooth but proximable terms. Using an operator splitting strategy, the objective is decomposed into subproblems that are conveniently, individually and simultaneously solved. With the assistance of the Moreau decomposition, our method excludes auxiliary variables that exist in the ADMM and possesses a compacter structure. Thus, the proposed method is preferable in distributed computation. The convergence proof and convergence rate analysis are presented. Application to both image restoration and image compressed sensing demonstrates the effectiveness and efficiency of the proposed method. © 2016 Elsevier Inc.
  Accession Number: 20163002624578
• Record 406 of
  
  Title:Perspective of monochromatic gamma-ray line detection with the High Energy cosmic-Radiation Detection (HERD) facility onboard China's space station
  
  Author(s):Huang, Xiaoyuan(1); Lamperstorfer, Anna S.(1); Tsai, Yue-Lin Sming(2); Xu, Ming(3); Yuan, Qiang(4); Chang, Jin(5); Dong, Yong-Wei(3); Hu, Bing-Liang(6); Lü, Jun-Guang(7); Wang, Le(6); Wu, Bo-Bing(3); Zhang, Shuang-Nan(3)
  Source: Astroparticle Physics  Volume: 78  Issue:   DOI: 10.1016/j.astropartphys.2016.02.003  Published: May 2016  
  Abstract:HERD is the High Energy cosmic-Radiation Detection instrument proposed to operate onboard China's space station in the 2020s. It is designed to detect energetic cosmic ray nuclei, leptons and photons with a high energy resolution (∼1% for electrons and photons and 20% for nuclei) and a large geometry factor (>3 m2 sr for electrons and diffuse photons and > [2]m2 sr for nuclei). In this work we discuss the capability of HERD to detect monochromatic γ-ray lines, based on simulations of the detector performance. It is shown that HERD will be one of the most sensitive instruments for monochromatic γ-ray searches at energies between ∼ 10 to a few hundred GeV. Above hundreds of GeV, Cherenkov telescopes will be more sensitive due to their large effective area. As a specific example, we show that a good portion of the parameter space of a supersymmetric dark matter model can be probed with HERD. © 2016 Elsevier B.V. All rights reserved.
  Accession Number: 20161002065241
• Record 407 of
  
  Title:Scalable quantum state generation using integrated frequency combs
  
  Author(s):Roztocki, Piotr(1); Kues, Michael(1); Reimer, Christian(1); Wetzel, Benjamin(1,2); Grazioso, Fabio(1); Little, Brent E.(3); Chu, Sai T.(4); Johnston, Tudor(1); Bromberg, Yaron(5); Caspani, Lucia(1,6); Moss, David J.(7); Morandotti, Roberto(1,8)
  Source: Optics InfoBase Conference Papers  Volume:   Issue:   DOI:   Published: 2016  
  Abstract:Optical quantum states are fundamental for applications in quantum information processing. We show that integrated frequency comb sources, operating in the quantum regime, can provide a scalable and versatile platform for quantum state generation. © OSA 2016.
  Accession Number: 20171403515709
• Record 408 of
  
  Title:Demonstration of bi- and multi-stability in a high order ring resonator
  
  Author(s):Jin, Li(1); Pasquazi, Alessia(2); Di Lauro, Luigi(2); Peccianti, Marco(2); Pun, Edwin Y.B.(1); Moss, David J.(3); Morandotti, Roberto(4); Little, Brent E.(5); Chu, Sai T.(1)
  Source: 2016 21st OptoElectronics and Communications Conference, OECC 2016 - Held Jointly with 2016 International Conference on Photonics in Switching, PS 2016  Volume:   Issue:   DOI:   Published: October 26, 2016  
  Abstract:We experimentally demonstrated the bistability and multi-stability in a 5th order cascaded CMOS compatible ring resonator. The shape evolution of the filter under different states is also investigated. © 2016 IEICE.
  Accession Number: 20164903083821