arXiv subjects

Rui Guo

Publications and source records attributed to Rui Guo.

At least 109 records · Page 6Linked to original sources

arXiv2019

DV3+HED+: A DCNNs-based Framework to Monitor Temporary Works and ESAs in Railway Construction Project Using VHR Satellite Images

Current VHR(Very High Resolution) satellite images enable the detailed monitoring of the earth and can capture the ongoing works of railway construction. In this paper, we present an integrated framework applied to monitoring the railway construction in China, using QuickBird, GF-2 and Google Earth VHR satellite images. We also construct a novel DCNNs-based (Deep Convolutional Neural Networks) semantic segmentation network to label the temporary works such as borrow & spoil area, camp, beam yard and ESAs(Environmental Sensitive Areas) such as resident houses throughout the whole railway construction project using VHR satellite images. In addition, we employ HED edge detection sub-network to refine the boundary details and attention cross entropy loss function to fit the sample class disequilibrium problem. Our semantic segmentation network is trained on 572 VHR true color images, and tested on the 15 QuickBird true color images along Ruichang-Jiujiang railway during 2015-2017. The experiment results show that compared with the existing state-of-the-art approach, our approach has obvious improvements with an overall accuracy of more than 80%.

cs.CV↗

arXiv2019

Spatio-Temporal Road Scene Reconstruction using Superpixel Markov Random Field

Scene model construction based on image rendering is an indispensable but challenging technique in computer vision and intelligent transportation systems. In this paper, we propose a framework for constructing 3D corridor-based road scene models. This consists of two successive stages: road detection and scene construction. The road detection is realized by a new superpixel Markov random field (MRF) algorithm. The data fidelity term in the MRF's energy function is jointly computed according to the superpixel features of color, texture and location. The smoothness term is established on the basis of the interaction of spatio-temporally adjacent superpixels. In the subsequent scene construction, the foreground and background regions are modeled independently. Experiments for road detection demonstrate the proposed method outperforms the state-of-the-art in both accuracy and speed. The scene construction experiments confirm that the proposed scene models show better correctness ratios, and have the potential to support a range of applications.

cs.CV↗

arXiv2019

Watt-level, kHz pulsed ASE source with pulse-width close to round-trip time based on Nd:GdVO4 bounce geometry

We demonstrate a watt-level, kHz nanosecond-pulse ASE source with its pulse-width being close to its round-trip time. The ASE uses a Nd:GdVO4 high gain bounce geometry structure without an output coupler. Using an EOQ (electro-optics Q-switch) device with high extinction-ratio, the pulse-width reaches 2.28, 1.73 and 1.17 ns under three effective cavity lengths, respectively. All these pulse-widths are close to the round-trip time of the corresponding effective cavity lengths. With the pulse-width being 1.17 ns, maximum output energy of 120 μJ and peak power of 100 kW are achieved. This study offers a convenient method to obtain high-peak-power short pulses, comparing with cavity-dumping method.

physics.optics↗

arXiv2019

Acoustic-optic Q-switched cavityless weak-feedback laser based on Nd:GdVO4 bounce geometry

An AOQ (acoustic-optic Q-switched) laser with cavityless weak-feedback configuration is demonstrated based on a Nd:GdVO4 bounce geometry. The laser can operate at a repetition up to 500 kHz with the output power above 4W. The pulse-width at 100 kHz reaches 5.2 ns, which is 4.3 times the round-trip time. A theory of Q-switched cavityless weak-feedback laser is proposed for the first time, to our best knowledge. This theory is very suitable for analyzing short pulses comparable to round-trip time. By utilizing the theory, simulation is implemented for our experimental conditions. The consistence between the simulation and the experimental results proves the validity of our theory.

physics.optics↗

arXiv2019

Short pulse close to round-trip time generated by cavityless high gain Nd:GdVO4 bounce geometry

In this paper, laser pulses with pulse-widths approach to the round-trip time are generated by utilizing a cavityless high gain Nd:GdVO4 bounce geometry. By adopting an EOQ (electro-optics Q-switch), pulse-widths of 1.36 ns, 1.82 ns, and 2.39 ns are achieved at three effective cavity lengths respectively. All these pulse-widths are close to the round-trip time of corresponding effective cavity lengths. Moreover, the output power reaches watt-level and the repetition rate is kHz-level, meanwhile the M2 factor is less than 1.3. Spectrally, the laser has a continuous spectrum with 10 dB linewidth of 0.2 nm.

physics.optics↗

arXiv2019

SIGNet: Semantic Instance Aided Unsupervised 3D Geometry Perception

Unsupervised learning for geometric perception (depth, optical flow, etc.) is of great interest to autonomous systems. Recent works on unsupervised learning have made considerable progress on perceiving geometry; however, they usually ignore the coherence of objects and perform poorly under scenarios with dark and noisy environments. In contrast, supervised learning algorithms, which are robust, require large labeled geometric dataset. This paper introduces SIGNet, a novel framework that provides robust geometry perception without requiring geometrically informative labels. Specifically, SIGNet integrates semantic information to make depth and flow predictions consistent with objects and robust to low lighting conditions. SIGNet is shown to improve upon the state-of-the-art unsupervised learning for depth prediction by 30% (in squared relative error). In particular, SIGNet improves the dynamic object class performance by 39% in depth prediction and 29% in flow prediction. Our code will be made available at https://github.com/mengyuest/SIGNet

cs.CV↗

arXiv2018

Multi-view Point Cloud Registration with Adaptive Convergence Threshold and its Application on 3D Model Retrieval

Multi-view point cloud registration is a hot topic in the communities of multimedia technology and artificial intelligence (AI). In this paper, we propose a framework to reconstruct the 3D models by the multi-view point cloud registration algorithm with adaptive convergence threshold, and subsequently apply it to 3D model retrieval. The iterative closest point (ICP) algorithm is implemented combining with the motion average algorithm for the registration of multi-view point clouds. After the registration process, we design applications for 3D model retrieval. The geometric saliency map is computed based on the vertex curvature. The test facial triangle is then generated based on the saliency map, which is applied to compare with the standard facial triangle. The face and non-face models are then discriminated. The experiments and comparisons prove the effectiveness of the proposed framework.

cs.CV↗

arXiv2018

Bose-Einstein Condensation in a Plasmonic Lattice

Bose-Einstein condensation is a remarkable manifestation of quantum statistics and macroscopic quantum coherence. Superconductivity and superfluidity have their origin in Bose-Einstein condensation. Ultracold quantum gases have provided condensates close to the original ideas of Bose and Einstein, while condensation of polaritons and magnons have introduced novel concepts of non-equilibrium condensation. Here, we demonstrate a Bose-Einstein condensate (BEC) of surface plasmon polaritons in lattice modes of a metal nanoparticle array. Interaction of the nanoscale-confined surface plasmons with a room-temperature bath of dye molecules enables thermalization and condensation in picoseconds. The ultrafast thermalization and condensation dynamics are revealed by an experiment that exploits thermalization under propagation and the open cavity character of the system. A crossover from BEC to usual lasing is realized by tailoring the band structure. This new condensate of surface plasmon lattice excitations has promise for future technologies due to its ultrafast, room-temperature and on-chip nature.

cond-mat.quant-gas↗

arXiv2018

Lasing at the K-points of a honeycomb plasmonic lattice

We study lasing at the high-symmetry points of the Brillouin zone in a honeycomb plasmonic lattice. We use symmetry arguments to define singlet and doublet modes at the $\Kp$-points of the reciprocal space. We experimentally demonstrate lasing at the $\Kp$-points \changed{that is based on plasmonic lattice modes and two-dimensional feedback}. By comparing polarization properties to \changed{$T$-matrix} simulations, we identify the lasing mode as one of the singlets with an energy minimum at the $\Kp$-point enabling feedback. Our results offer prospects for studies of topological lasing in radiatively coupled systems.

cond-mat.mes-hall↗

arXiv2018

SDSS-IV MaNGA: pattern speeds of barred galaxies

The MaNGA project has obtained IFU data for several thousand nearby galaxies, including barred galaxies. With the two dimensional spectral and kinematic information provided by IFUs, we can measure the pattern speed of a barred galaxy, which determines the bar dynamics. We apply the non-parametric method proposed by Tremaine \& Weinberg to estimate the bar pattern speed for 53 barred galaxies, making this the largest sample studied so far in this way. Our sample is selected from the MaNGA first public data release as part of SDSS Data Release 13 according mainly to the axis ratio and position angle difference between the bar and disc, while kinematic data is from the later SDSS Data Release 14. We have used both the photometric position angle from the photometric image and the kinematic position angle from the stellar velocity map to derive the pattern speed. Combining three independent bar length measurements and the circular velocity from Jeans Anisotropic modelling (JAM), we also determine the dimensionless ratio $\cal{R}$ of the corotation radius to the bar length. We find that the galaxy's position angle is the main uncertainty in determining the bar pattern speed. The kinematic position angle leads to fewer ultrafast bars than the photometric position angle, and this could be due to the method of measuring the kinematic position angle. We study the dependence of $\cal{R}$ values on galaxy properties such as the dark matter fraction from JAM modelling and the stellar age and metallicity from stellar population synthesis (SPS). A positive correlation between the bar length and bar strength is found: the longer the bar, the stronger the bar. However, no other significant correlations are found. This may result from errors in deriving the $\cal{R}$ values or from the complex formation and slowdown processes of galactic bars.

astro-ph.GA↗

arXiv2017

Probing satellite galaxies in the Local Group by using FAST

The abundance of neutral hydrogen (HI) in satellite galaxies in the Local Group is important for studying the formation history of our Local Group. In this work, we generated mock HI satellite galaxies in the Local Group using the high mass resolution hydrodynamic \textsc{apostle} simulation. The simulated HI mass function agrees with the ALFALFA survey very well above $10^6M_{\odot}$, although there is a discrepancy below this scale because of the observed flux limit. After carefully checking various systematic elements in the observations, including fitting of line width, sky coverage, integration time, and frequency drift due to uncertainty in a galaxy's distance, we predicted the abundance of HI in galaxies in a future survey that will be conducted by FAST. FAST has a larger aperture and higher sensitivity than the Arecibo telescope. We found that the HI mass function could be estimated well around $10^5 M_{\odot}$ if the integration time is 40 minutes. Our results indicate that there are 61 HI satellites in the Local Group, and 36 in the FAST field above $10^5 M_{\odot}$. This estimation is one order of magnitude better than the current data, and will put a strong constraint on the formation history of the Local Group. Also more high resolution simulated samples are needed to achieve this target.

astro-ph.GA↗

arXiv2017

Driver Action Prediction Using Deep (Bidirectional) Recurrent Neural Network

Advanced driver assistance systems (ADAS) can be significantly improved with effective driver action prediction (DAP). Predicting driver actions early and accurately can help mitigate the effects of potentially unsafe driving behaviors and avoid possible accidents. In this paper, we formulate driver action prediction as a timeseries anomaly prediction problem. While the anomaly (driver actions of interest) detection might be trivial in this context, finding patterns that consistently precede an anomaly requires searching for or extracting features across multi-modal sensory inputs. We present such a driver action prediction system, including a real-time data acquisition, processing and learning framework for predicting future or impending driver action. The proposed system incorporates camera-based knowledge of the driving environment and the driver themselves, in addition to traditional vehicle dynamics. It then uses a deep bidirectional recurrent neural network (DBRNN) to learn the correlation between sensory inputs and impending driver behavior achieving accurate and high horizon action prediction. The proposed system performs better than other existing systems on driver action prediction tasks and can accurately predict key driver actions including acceleration, braking, lane change and turning at durations of 5sec before the action is executed by the driver.

stat.ML↗

arXiv2017

Weighted Motion Averaging for the Registration of Multi-View Range Scans

Multi-view registration is a fundamental but challenging problem in 3D reconstruction and robot vision. Although the original motion averaging algorithm has been introduced as an effective means to solve the multi-view registration problem, it does not consider the reliability and accuracy of each relative motion. Accordingly, this paper proposes a novel motion averaging algorithm for multi-view registration. Firstly, it utilizes the pair-wise registration algorithm to estimate the relative motion and overlapping percentage of each scan pair with a certain degree of overlap. With the overlapping percentage available, it views the overlapping percentage as the corresponding weight of each scan pair and proposes the weight motion averaging algorithm, which can pay more attention to reliable and accurate relative motions. By treating each relative motion distinctively, more accurate registration can be achieved by applying the weighted motion averaging to multi-view range scans. Experimental results demonstrate the superiority of our proposed approach compared with the state-of-the-art methods in terms of accuracy, robustness and efficiency.

cs.CV↗

arXiv2016

A Novel Artificial Fish Swarm Algorithm for Pattern Recognition with Convex Optimization

Image pattern recognition is an important area in digital image processing. An efficient pattern recognition algorithm should be able to provide correct recognition at a reduced computational time. Off late amongst the machine learning pattern recognition algorithms, Artificial fish swarm algorithm is one of the swarm intelligence optimization algorithms that works based on population and stochastic search. In order to achieve acceptable result, there are many parameters needs to be adjusted in AFSA. Among these parameters, visual and step are very significant in view of the fact that artificial fish basically move based on these parameters. In standard AFSA, these two parameters remain constant until the algorithm termination. Large values of these parameters increase the capability of algorithm in global search, while small values improve the local search ability of the algorithm. In this paper, we empirically study the performance of the AFSA and different approaches to balance between local and global exploration have been tested based on the adaptive modification of visual and step during algorithm execution. The proposed approaches have been evaluated based on the four well-known benchmark functions. Experimental results show considerable positive impact on the performance of AFSA. A Convex optimization has been integrated into the proposed work to have an ideal segmentation of the input image which is a MR brain image.

cs.CV↗

arXiv2016

Generation of concatenated Greenberger-Horne-Zeilinger-type entangled coherent state based on linear optics

The concatenated Greenberger-Horne-Zeilinger (C-GHZ) state is a new type of multipartite entangled state, which has potential application in future quantum information. In this paper, we propose a protocol of constructing arbitrary C-GHZ entangled state approximatively. Different from the previous protocols, each logic is encoded in the coherent state. This protocol is based on the linear optics, which is feasible in experimental technology. This protocol may be useful in quantum information based on the C-GHZ state.

quant-ph↗

arXiv2016

The Evolution of Advanced Merger (U)LIRGs on the Color-Stellar Mass Diagram

Based on a sample of 79 local advanced merger (adv-merger) (U)LIRGs, we search for the evidence of quenching process by investigating the distributions of the star formation history indicators (EW(H$α$), EW(H$δ$$_A$) and D$_n(4000)$) on the NUV-r color-mass and SFR-$M_{\ast}$ diagrams. The distributions of the EW(H$α$) and D$_n(4000)$ on the NUV-r color-mass diagram show clear trends that at a given stellar mass, galaxies with redder NUV-r colors have smaller EW(H$α$) and larger D$_n(4000)$. The reddest adv-merger (U)LIRGs close to the green valley have D$_n(4000)$$>1.4$ mostly. In addition, in the SFR-$M_{\ast}$ diagram, as the SFR decreases, the EW(H$α$) decreases and the D$_n(4000)$ increases, implying that the adv-merger (U)LIRGs on the star formation main sequence have more evolved stellar populations than those above the main sequence. These results indicate that a fraction of the adv-merger (U)LIRGs have already exhibited signs of fading from the starburst phase and that the NUV-r reddest adv-merger (U)LIRGs are likely at the initial stage of post-starbursts with age of $\sim 1$ Gyr, which is consistent with the gas exhausting time-scales. Therefore, our results offer additional support for the fast evolutionary track from the blue cloud to the red sequence.

astro-ph.GA↗

arXiv2016

The role of major gas-rich mergers on the evolution of galaxies from the blue cloud to the red sequence

With the aim of exploring the fast evolutionary path from the blue cloud of star-forming galaxies to the red sequence of quiescent galaxies in the local universe, we select a local advanced merging infrared luminous and ultraluminous galaxy (adv-merger (U)LIRGs) sample and perform careful dust extinction corrections to investigate their positions in the SFR-$M_{\ast}$, u-r and NUV-r color-mass diagrams. The sample consists of 89 (U)LIRGs at the late merger stage, obtained from cross-correlating the IRAS Point Source Catalog Redshift Survey and 1 Jy ULIRGs samples with the Sloan Digital Sky Survey DR7 database. Our results show that $74\%\pm 5\%$ of adv-merger (U)LIRGs are localized above the $1\, σ$ line of the local star-forming galaxy main sequence. We also find that all adv-merger (U)LIRGs are more massive than and as blue as the blue cloud galaxies after corrections of Galactic and internal dust extinctions, with $95\%\pm 2\%$ and $81\%\pm 4\%$ of them outside the blue cloud on the u-r and NUV-r color-mass diagrams, respectively. These results, combined with the short timescale for exhausting the molecular gas reservoir in adv-merger (U)LIRGs ($3\times 10^{7}$ to $3\times 10^{8}$ years), imply that the adv-merger (U)LIRGs are likely at the starting point of the fast evolutionary track previously proposed by several groups. While the number density of adv-merger (U)LIRGs is only $\sim 0.1\%$ of the blue cloud star-forming galaxies in the local universe, this evolutionary track may play a more important role at high redshift.

astro-ph.GA↗

arXiv2016

Liquid-Gated High Mobility and Quantum Oscillation of the Two-Dimensional Electron Gas at an Oxide Interface

Electric field effect in electronic double layer transistor (EDLT) configuration with ionic liquids as the dielectric materials is a powerful means of exploring various properties in different materials. Here we demonstrate the modulation of electrical transport properties and extremely high mobility of two-dimensional electron gas at LaAlO$_3$/SrTiO$_3$ (LAO/STO) interface through ionic liquid-assisted electric field effect. By changing the gate voltages, the depletion of charge carrier and the resultant enhancement of electron mobility up to 19380 cm$^2$/Vs are realized, leading to quantum oscillations of the conductivity at the LAO/STO interface. The present results suggest that high-mobility oxide interfaces which exhibit quantum phenomena could be obtained by ionic liquid-assisted field effect.

cond-mat.str-el↗