arXiv subjects

Yan Zhang

Publications and source records attributed to Yan Zhang.

At least 649 records · Page 36Linked to original sources

arXiv2018

A Novel Low-cost FPGA-based Real-time Object Tracking System

In current visual object tracking system, the CPU or GPU-based visual object tracking systems have high computational cost and consume a prohibitive amount of power. Therefore, in this paper, to reduce the computational burden of the Camshift algorithm, we propose a novel visual object tracking algorithm by exploiting the properties of the binary classifier and Kalman predictor. Moreover, we present a low-cost FPGA-based real-time object tracking hardware architecture. Extensive evaluations on OTB benchmark demonstrate that the proposed system has extremely compelling real-time, stability and robustness. The evaluation results show that the accuracy of our algorithm is about 48%, and the average speed is about 309 frames per second.

cs.CV↗

arXiv2018

A Novel Parallel Ray-Casting Algorithm

The Ray-Casting algorithm is an important method for fast real-time surface display from 3D medical images. Based on the Ray-Casting algorithm, a novel parallel Ray-Casting algorithm is proposed in this paper. A novel operation is introduced and defined as a star operation, and star operations can be computed in parallel in the proposed algorithm compared with the serial chain of star operations in the Ray-Casting algorithm. The computation complexity of the proposed algorithm is reduced from $O(n)$ to $O(\log^n_2)$.

cs.CV↗

arXiv2018

A New Decidable Class of Tuple Generating Dependencies: The Triangularly-Guarded Class

In this paper we introduce a new class of tuple-generating dependencies (TGDs) called triangularly-guarded TGDs, which are TGDs with certain restrictions on the atomic derivation track embedded in the underlying rule set. We show that conjunctive query answering under this new class of TGDs is decidable. We further show that this new class strictly contains some other decidable classes such as weak-acyclic, guarded, sticky and shy, which, to the best of our knowledge, provides a unified representation of all these aforementioned classes.

cs.AI↗

arXiv2018

An Integrated Optimization + Learning Approach to Optimal Dynamic Pricing for the Retailer with Multi-type Customers in Smart Grids

In this paper, we consider a realistic and meaningful scenario in the context of smart grids where an electricity retailer serves three different types of customers, i.e., customers with an optimal home energy management system embedded in their smart meters (C-HEMS), customers with only smart meters (C-SM), and customers without smart meters (C-NONE). The main objective of this paper is to support the retailer to make optimal day-ahead dynamic pricing decisions in such a mixed customer pool. To this end, we propose a two-level decision-making framework where the retailer acting as upper-level agent firstly announces its electricity prices of next 24 hours and customers acting as lower-level agents subsequently schedule their energy usages accordingly. For the lower level problem, we model the price responsiveness of different customers according to their unique characteristics. For the upper level problem, we optimize the dynamic prices for the retailer to maximize its profit subject to realistic market constraints. The above two-level model is tackled by genetic algorithms (GA) based distributed optimization methods while its feasibility and effectiveness are confirmed via simulation results.

eess.SY↗

arXiv2018

Temporal Human Action Segmentation via Dynamic Clustering

We present an effective dynamic clustering algorithm for the task of temporal human action segmentation, which has comprehensive applications such as robotics, motion analysis, and patient monitoring. Our proposed algorithm is unsupervised, fast, generic to process various types of features, and applicable in both the online and offline settings. We perform extensive experiments of processing data streams, and show that our algorithm achieves the state-of-the-art results for both online and offline settings.

cs.CV↗

arXiv2018

SLADS-Net: Supervised Learning Approach for Dynamic Sampling using Deep Neural Networks

In scanning microscopy based imaging techniques, there is a need to develop novel data acquisition schemes that can reduce the time for data acquisition and minimize sample exposure to the probing radiation. Sparse sampling schemes are ideally suited for such applications where the images can be reconstructed from a sparse set of measurements. In particular, dynamic sparse sampling based on supervised learning has shown promising results for practical applications. However, a particular drawback of such methods is that it requires training image sets with similar information content which may not always be available. In this paper, we introduce a Supervised Learning Approach for Dynamic Sampling (SLADS) algorithm that uses a deep neural network based training approach. We call this algorithm SLADS- Net. We have performed simulated experiments for dynamic sampling using SLADS-Net in which the training images either have similar information content or completely different information content, when compared to the testing images. We compare the performance across various methods for training such as least- squares, support vector regression and deep neural networks. From these results we observe that deep neural network based training results in superior performance when the training and testing images are not similar. We also discuss the development of a pre-trained SLADS-Net that uses generic images for training. Here, the neural network parameters are pre-trained so that users can directly apply SLADS-Net for imaging experiments.

eess.SP↗

arXiv2018

Learning to Count Objects in Natural Images for Visual Question Answering

Visual Question Answering (VQA) models have struggled with counting objects in natural images so far. We identify a fundamental problem due to soft attention in these models as a cause. To circumvent this problem, we propose a neural network component that allows robust counting from object proposals. Experiments on a toy task show the effectiveness of this component and we obtain state-of-the-art accuracy on the number category of the VQA v2 dataset without negatively affecting other categories, even outperforming ensemble models with our single model. On a difficult balanced pair metric, the component gives a substantial improvement in counting over a strong baseline by 6.6%.

cs.CV↗

arXiv2018

Controllable unidirectional transport and photon storage in an one-dimensional lattice with complex hopping rates

We study an one-dimensional non-Hermitian lattice with complex hopping rates, which can be realized by a quasi-one-dimensional sawtooth-type Hermitian lattice after adiabatic elimination with proper conditions. By means of synthetic magnetic fluxes, the imaginary parts of the complex hopping rates can be modulated by additional phase, thus a non-reciprocal structure arises. With this lattice, one can realize robust unidirectional transport for both single-site and Gaussian excitations, which is immune to defects and backscattering. Furthermore, we proposed a sandwich structure based on the non-Hermitian lattice, which can be used for realizing controllable photon storage and reversal. The storage time and range can be artificially controlled within limits, and the storage efficiency can be increased via a finite gain compensation. The proposal of controllable photon transport in this paper opens up a new path for unidirectional photon transport and provides a promising platform for optical control and manipulation.

quant-ph↗

arXiv2018

Distributed Hierarchical Control for State Estimation With Robotic Sensor Networks

This paper addresses active state estimation with a team of robotic sensors. The states to be estimated are represented by spatially distributed, uncorrelated, stationary vectors. Given a prior belief on the geographic locations of the states, we cluster the states in moderately sized groups and propose a new hierarchical Dynamic Programming (DP) framework to compute optimal sensing policies for each cluster that mitigates the computational cost of planning optimal policies in the combined belief space. Then, we develop a decentralized assignment algorithm that dynamically allocates clusters to robots based on the pre-computed optimal policies at each cluster. The integrated distributed state estimation framework is optimal at the cluster level but also scales very well to large numbers of states and robot sensors. We demonstrate efficiency of the proposed method in both simulations and real-world experiments using stereoscopic vision sensors.

cs.RO↗

arXiv2018

Controlling a Robotic Stereo Camera Under Image Quantization Noise

In this paper, we address the problem of controlling a mobile stereo camera under image quantization noise. Assuming that a pair of images of a set of targets is available, the camera moves through a sequence of Next-Best-Views (NBVs), i.e., a sequence of views that minimize the trace of the targets' cumulative state covariance, constructed using a realistic model of the stereo rig that captures image quantization noise and a Kalman Filter (KF) that fuses the observation history with new information. The proposed algorithm decomposes control into two stages: first the NBV is computed in the camera relative coordinates, and then the camera moves to realize this view in the fixed global coordinate frame. This decomposition allows the camera to drive to a new pose that effectively realizes the NBV in camera coordinates while satisfying Field-of-View constraints in global coordinates, a task that is particularly challenging using complex sensing models. We provide simulations and real experiments that illustrate the ability of the proposed mobile camera system to accurately localize sets of targets. We also propose a novel data-driven technique to characterize unmodeled uncertainty, such as calibration errors, at the pixel level and show that this method ensures stability of the KF.

cs.RO↗

arXiv2018

A study of the new hemispherical 9-inch PMT

The new hemispherical photomultiplier tubes (PMTs) with 9 inch diameter from Hainan Zhanchuang Photonics Technology Co.,Ltd (HZC) have been studied. Narrow transit time spread (FWHM=2.35 ns) accompanied by small nonlinearity (750 photoelectrons at 5%) and high gain (1E7 ) with good single photoelectron (PE) resolution have been observed. 11 PMTs of this type are deployed and studied in the prototype detector for JUNO at IHEP, China.

physics.ins-det↗

arXiv2018

All-optical photon transmission switching in a passive-active optomechanical system

We propose a feasible scheme to realize all-optical photon transmission switching in a passiveactive optomechanical system, consisting of one ordinary passive cavity, one active cavity and one common movable membrane oscillator of perfect reflection, driven by two strong control fields and two weak probe fields symmetrically. By means of the gain effect of the active cavity, many novel and valuable phenomena arise, such as frequency-independent perfect reflection (FIPR) first proposed in this paper, adjustable photon bidirectional transmission, phase-dependent non-reciprocity and so on. The relevant parameters used for controlling the all-optical switching are precisely tunable by adjusting the strengths of control fields and the relative phase of probe fields. Furthermore, tunable fast and slow light can be realized in our system by accurately adjusting relevant parameters which is readily and feasible in experiments. These novel phenomena originate from the effective optomechanical coupling and the gain effect provide a promising platform for photonic devices, quantum network node fabrication and quantum information process (QIP).

quant-ph↗

arXiv2017

An Efficient NPN Boolean Matching Algorithm Based on Structural Signature and Shannon Expansion

An efficient pairwise Boolean matching algorithm to solve the problem of matching single-output specified Boolean functions under input negation and/or input permutation and/or output negation (NPN) is proposed in this paper. We present the Structural Signature (SS) vector, which is composed of a 1st signature value, two symmetry marks, and a group mark. As a necessary condition for NPN Boolean matching, the structural signature is more effective than is the traditional signature. Two Boolean functions, f and g, may be equivalent when they have the same SS vector. The symmetry mark can distinguish symmetric variables and asymmetric variables and search multiple variable mappings in a single variable-mapping search operation, which reduces the search space significantly. Updating the SS vector using Shannon decomposition provides benefits in distinguishing unidentified variables, and the group mark and the phase collision check discover incorrect variable mappings quickly, which also speeds up the NPN Boolean matching process. Using the algorithm proposed in this paper, we tested both equivalent and non-equivalent matching peeds on the MCNC benchmark circuit sets and the random circuit sets. In the experiment, our algorithm is two times faster than competitors when testing equivalent circuits and averages at least one hundred times faster when testing non-equivalent circuits. The experimental results show that our approach is highly effective in solving the NPN Boolean matching problem.

cs.DS↗

arXiv2017

Flattening axial intensity oscillations of a diffracted Bessel beam through a cardioid-like hole

We present a new feasible way to flatten the axial intensity oscillations for diffraction of a finite-sized Bessel beam, through designing a cardioid-like hole. The boundary formula of the cardioid-like hole is given analytically. Numerical results by the complete Rayleigh-Sommerfeld method reveal that the Bessel beam propagates stably in a considerably long axial range, after passing through the cardioid-like hole. Compared with the gradually absorbing apodization technique in previous papers, in this paper a hard truncation of the incident Bessel beam is employed at the cardioid-like hole edges. The proposed hard apodization technique takes two advantages in suppressing the axial intensity oscillations, i.e., easier implementation and higher accuracy. It is expected to have practical applications in laser machining, light sectioning, or optical trapping.

physics.optics↗

arXiv2017

A Prediction Model of the Project Life-span in Open Source Software Ecosystem

In nature ecosystems, animal life-spans are determined by genes and some other biological characteristics. Similarly, the software project life-spans are related to some internal or external characteristics. Analyzing the relations between these characteristics and the project life-span, may help developers, investors, and contributors to control the development cycle of the software project. The paper provides an insight on the project life-span for a free open source software ecosystem. The statistical analysis of some project characteristics in GitHub is presented, and we find that the choices of programming languages, the number of files, the label format of the project, and the relevant membership expressions can impact the life-span of a project. Based on these discovered characteristics, we also propose a prediction model to estimate the project life-span in open source software ecosystems. These results may help developers reschedule the project in open source software ecosystem.

cs.SE↗

arXiv2017

Topic-based Integrator Matching for Pull Request

Pull Request (PR) is the main method for code contributions from the external contributors in GitHub. PR review is an essential part of open source software developments to maintain the quality of software. Matching a new PR for an appropriate integrator will make the PR reviewing more effective. However, PR and integrator matching are now organized manually in GitHub. To make this process more efficient, we propose a Topic-based Integrator Matching Algorithm (TIMA) to predict highly relevant collaborators(the core developers) as the integrator to incoming PRs . TIMA takes full advantage of the textual semantics of PRs. To define the relationships between topics and collaborators, TIMA builds a relation matrix about topic and collaborators. According to the relevance between topics and collaborators, TIMA matches the suitable collaborators as the PR integrator.

cs.SE↗

arXiv2017

Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55

We introduce a large-scale 3D shape understanding benchmark using data and annotation from ShapeNet 3D object database. The benchmark consists of two tasks: part-level segmentation of 3D shapes and 3D reconstruction from single view images. Ten teams have participated in the challenge and the best performing teams have outperformed state-of-the-art approaches on both tasks. A few novel deep learning architectures have been proposed on various 3D representations on both tasks. We report the techniques used by each team and the corresponding performances. In addition, we summarize the major discoveries from the reported results and possible trends for the future work in the field.

cs.CV↗

arXiv2017

Vignetting effect in Fourier ptychographic microscopy

Fourier ptychographic microscopy (FPM) is a computational imaging technique that overcomes the physical space-bandwidth product (SBP) limit of a conventional microscope by applying angular diversity illuminations. In the usual model of FPM, the microscopic system is approximated by being taken as space-invariant with transfer function determined by a complex pupil function of the objective. However, in real experimental conditions, several unexpected "semi-bright and semi-dark" images with strong vignetting effect can be easily observed when the sample is illuminated by the LED within the "transition zone" between bright field and dark field. These imperfect images, apparently, are not coincident with the space-invariant model and could deteriorate the reconstruction quality severely. In this Letter, we examine the impact of this space-invariant approximation on FPM image formation based on ray-based and rigorous wave optics-based analysis. Our analysis shows that for a practical FPM microscope with a low power objective and a large field of view, the space invariance is destroyed by diffraction at other stops associated with different lens elements to a large extent. A modified version of the space-variant model is derived and discussed. Two simple countermeasures are also presented and experimentally verified to bypass or partially alleviate the vignetting-induced reconstruction artifacts.

physics.optics↗