Face verification with balanced thresholds.

The process of face verification is guided by a pre-learned global threshold, which, however, is often inconsistent with class-specific optimal thresholds. It is, hence, beneficial to pursue a balance of the class-specific thresholds in the model-learning stage. In this paper, we present a new dimensionality reduction algorithm tailored to the verification task that ensures threshold balance. This is achieved by the following aspects. First, feasibility is guaranteed by employing an affine transformation matrix, instead of the conventional projection matrix, for dimensionality reduction, and, hence, we call the proposed algorithm threshold balanced transformation (TBT). Then, the affine transformation matrix, constrained as the product of an orthogonal matrix and a diagonal matrix, is optimized to improve the threshold balance and classification capability in an iterative manner. Unlike most algorithms for face verification which are directly transplanted from face identification literature, TBT is specifically designed for face verification and clarifies the intrinsic distinction between these two tasks. Experiments on three benchmark face databases demonstrate that TBT significantly outperforms the state-of-the-art subspace techniques for face verification.     

Client-specific A-stack model for adult face verification across aging

The problem of time validity of biometric models has received only a marginal attention from researchers. In this paper, we propose to manage the aging influence on the adult face verification system by an A-stack age modeling technique, which uses the age as a class-independent metadata quality measure together with scores from a single or multiple baseline classifiers, in order to obtain better face verification performance. This allows for improved long-term class separation by introducing a dynamically changing decision boundary across the age progression in the scores-age space using a short-term enrollment model. This new method, based on the concept of classifier stacking and age-aware decision boundary, compares favorably with the conventional face verification approach, which uses age-independent decision threshold calculated only in the score space at the time of enrollment. Our experiments on the YouTube and MORPH data show that the use of the proposed approach allows for improving the identification accuracy as opposed to the baseline classifier.     

Face verification based on deep Bayesian convolutional neural network in unconstrained environment

Unconstrained face verification aims to verify whether two specify images contain the same person. In this paper, we propose a deep Bayesian convolutional neural network (DBCNN) framework to extract facial features and measure their similarity for face verification in unconstrained conditions. Specifically, we design a deep convolutional neural network and construct a Bayesian probabilistic model by transferring the Bayesian likelihood ratio function into linear decision function. By training a decision line rather than finding a suitable threshold, we further enlarge the distances between inter-class and intra-class in unconstrained environment. Finally, we comprehensively evaluate our method on LFW, CACD-VS and MegaFace datasets. The test results on LFW and CACD-VS datasets show that our method can shrink intra-class variations significantly. The performance of our DBCNN model on MegaFace dataset proves that our model can achieve comparable performance to state-of-the-art methods on face verification with relative small training data and only one single network.     

Face age classification based on a deep hybrid model

Face age estimation, a computer vision task facing numerous challenges due to its potential applications in identity authentication, human–computer interface, video retrieval and robot vision, has been attracting increasing attention. In recent years, the deep convolutional neural networks (DCNN) have achieved state-of-the-art performance in age classification of face images. We propose a deep hybrid framework for age classification by exploiting DCNN as the raw feature extractor along with several effective methods, including fine-tuning the DCNN into a fine-tuned deep age feature extraction (FDAFE) model, introducing a new method of feature extracting, applying the maximum joint probability classifier to age classification and a strategy to incorporate information from face images more effectively to improve estimation capabilities further. In addition, we pre-process the original image to represent age information more accurately. Based on the discriminative and compact framework, state-of-the-art performance on several face image data sets has been achieved in terms of classification accuracy.     

FuseKin: Weighted image fusion based kinship verification under unconstrained age group

Kinship verification using facial images is mainly performed with a single face sample per person. To perform with a single sample, it is very difficult to specify an age group where kin pairs may have higher similarities. To address the above problem, we propose a novel weighted multi sample fusion (WMSF) method. The proposed WMSF method combines kin signals present in multiple samples per person (MSPP) to form a FuseKin image. To select the most discriminant features from the extracted feature vector, we propose a patch based discriminative analysis (PDA) method. Weights are calculated using the PDA method so as to reduce the discrimination between positive FuseKin pairs. Experiments were conducted on two different datasets which contain multiple face image samples per person, namely Family101 and Family in the Wild (FIW) to validate the performance of the proposed methods. Our method achieves competitive results as compared to other state-of-the-art methods.     

非受限条件下双流增强浅层网络人脸年龄估计

针对非受限条件下人脸遮挡、光照不均、表情复杂、姿态各异等影响年龄估计精确率低的问题,提出一种非受限条件下双流增强浅层网络的人脸年龄估计(E2-doubleNet)算法.首先,在E2-doubleNet设计中采用了两个异构的单流浅层卷积神经网络模型以提高网络的学习能力;然后,在两个模型中采用不同的激活函数和池化层,增强网...     

惯性平面下基于Gabor滤波和视网膜模型的目标检测

本文给出了一个在复杂背景下定位目标的方案。首先用欧几里德距离映射(EDM)算法和形态操作对特征惯性平面做骨架化操作，然后用Gabor滤波器组检测骨架图象中指定形状的区域，该形状的真实性则用改进的视网膜模型来验证。实验结果证明该方法是行之有效的。     

Formulating face verification with semidefinite programming.

This paper presents a unified solution to three unsolved problems existing in face verification with subspace learning techniques: selection of verification threshold, automatic determination of subspace dimension, and deducing feature fusing weights. In contrast to previous algorithms which search for the projection matrix directly, our new algorithm investigates a similarity metric matrix (SMM). With a certain verification threshold, this matrix is learned by a semidefinite programming approach, along with the constraints of the kindred pairs with similarity larger than the threshold, and inhomogeneous pairs with similarity smaller than the threshold. Then, the subspace dimension and the feature fusing weights are simultaneously inferred from the singular value decomposition of the derived SMM. In addition, the weighted and tensor extensions are proposed to further improve the algorithmic effectiveness and efficiency, respectively. Essentially, the verification is conducted within an affine subspace in this new algorithm and is, hence, called the affine subspace for verification (ASV). Extensive experiments show that the ASV can achieve encouraging face verification accuracy in comparison to other subspace algorithms, even without the need to explore any parameters.     

Velocity-image model for online signature verification.

In general, online signature capturing devices provide outputs in the form of shape and velocity signals. In the past, strokes have been extracted while tracking velocity signal minimas. However, the resulting strokes are larger and complicated in shape and thus make the subsequent job of generating a discriminative template difficult. We propose a new stroke-based algorithm that splits velocity signal into various bands. Based on these bands, strokes are extracted which are smaller and more simpler in nature. Training of our proposed system revealed that low- and high-velocity bands of the signal are unstable, whereas the medium-velocity band can be used for discrimination purposes. Euclidean distances of strokes extracted on the basis of medium velocity band are used for verification purpose. The experiments conducted show improvement in discriminative capability of the proposed stroke-based system.     

Computer-aided verification

Theorem proving and model checking are powerful tools that can verify the logical correctness of today's ICs or find their hidden bugs. Today, the first computer-aided verification tools are becoming commercially available. They are based on methods that in many cases can reduce the complexity of verification (without sacrificing guaranteed correctness) to such a degree that it becomes computationally feasible. Among the most powerful of these methods are symbolic model-checking and homomorphic reduction, both of which represent a complex system in terms of a compact and computationally more tractable structure. Moreover, the two can be used together with a multiplicative reduction effect, since they work independently of one another. Of special importance is the fact that they each can be implemented automatically, so the task of reduction is programmed into the computer rather than presenting a burden to the design engineer     

Face recognition using recursive Fisher linear discriminant.

Fisher linear discriminant (FLD) has recently emerged as a more efficient approach for extracting features for many pattern classification problems as compared to traditional principal component analysis. However, the constraint on the total number of features available from FLD has seriously limited its application to a large class of problems. In order to overcome this disadvantage, a recursive procedure of calculating the discriminant features is suggested in this paper. The new algorithm incorporates the same fundamental idea behind FLD of seeking the projection that best separates the data corresponding to different classes, while in contrast to FLD the number of features that may be derived is independent of the number of the classes to be recognized. Extensive experiments of comparing the new algorithm with the traditional approaches have been carried out on face recognition problem with the Yale database, in which the resulting improvement of the performances by the new feature extraction scheme is significant.     

Experimental verification of mode shape in s.a.w. grating resonators

Gratings of finite width provide wave guidance by means of reflection from the grating boundaries. Measured mode patterns are compared with the theoretically predicted patterns, and good agreement is found.     

基于VMM统一验证平台的Serdes芯片验证

本文基于VMM验证平台,介绍了高速串行收发器芯片的验证方法。文章首先简要介绍了Serdes芯片和VMM验证方法,然后搭建了Serdes芯片的VMM统一验证平台,并从测试激励产生、寄存器读写控制、覆盖率自动统计、断言验证及覆盖率收敛等几个方面详细阐述了Serdes芯片的验证过程。最后给出了验证结果和测试报告。     

光学设计自动化软件验证技术概述

在计算机辅助设计软件中，光学设计自动化软件是随着微光子学、光电子学和深亚微米集成电路的发展而逐渐产业化的，相对于电子设计自动化软件而言，仍有许多有待完善和改进的地方。在验证方面主要从原理验证、合理性验证和实验验证来保证光学设计自动化软件的正确性和质量。同时也给出了相关的实例。     

Provable data possession scheme based on public verification and private verification

More and more users choose to transfer their applications and data into the cloud.Data security is a key issue for cloud storage systems.To ensure the integrity and validity of the data stored in the cloud,provable data possession (PDP) scheme is particularly important.In order to verify whether the cloud storage service provider had stored the data of the user completely,a scheme on the basis of NRPDP (non-repudiable PDP) was improved and extended,and a data retention scheme based on public authentication and private authentication was proposed.The scheme can verify the trustworthiness of the service provider and the user in the cloud storage at the same time,which satisfies the non-repudiation of the verification.The theory proves the non-repudiation of the proposed scheme.The experiment proves that the efficiency of each stage is better than that of the existing single public verification method or private authentication method.     

拥有新面子

美丽是由30％的天生再加上70％的装扮而完成的。如何让你的脸看起来更健康更漂亮。除了正常的作息时间和注意自我心理调节随时保持良好的心情以外,对面部做一些适当的护理也是必不可少的。在此我们为你将精心整理出了脸部的保养护理基本方法,这都是在平常生活中可以轻松实现的。     

Speaker verification using signatures

An automatic speaker verification system is investigated as a means of reinforcing speech recognition security. The system's implementation is independent of speaker population size. Given clean speech and a five digit code, 91.3% of impostor attempts at breaching security are thwarted. The corresponding figure for coded speech is 88.2%     

Automatic on-line signature verification

Automatic on-line signature verification is an intriguing intellectual challenge with many practical applications. I review the context of this problem and then describe my own approach to it, which breaks with tradition by relying primarily on the detailed shape of a signature for its automatic verification, rather than relying primarily on the pen dynamics during the production of the signature. I propose a robust, reliable, and elastic local-shape-based model for handwritten on-line curves; this model is generated by first parameterizing each on-line curve over its normalized arc-length and then representing along the length of the curve, in a moving coordinate frame, measures of the curve within a sliding window that are analogous to the position of the center of mass, the torque exerted by a force, and the moments of inertia of a mass distribution about its center of mass. Further I suggest the weighted and biased harmonic mean as a graceful mechanism of combining errors from multiple models of which at least one model is applicable but not necessarily more than one model is applicable, recommending that each signature be represented by multiple models, these models, perhaps, local and global, shape based and dynamics based. Finally, I outline a signature-verification algorithm that I have implemented and tested successfully both on databases and in live experiments     

Protocols for watermark verification

In current digital watermarking schemes used to deter piracy of multimedia content, the owner typically reveals the watermark in the process of establishing piracy. Once revealed, a watermark can be removed. We eliminate this limitation by using cryptographic protocols to demonstrate the presence of a watermark without revealing it     

使用荧光光谱分析法(XRF)进行RoHS验证

随着欧盟RoHS最后期限的临近,很多公司都开始采用无铅化工艺,但要确保工艺的一致性,有效的检测方法是必不可缺的,荧光光谱分析法（XRF）就是其中之一。许多晶圆制造厂已开始用XRF法在薄镀层上进行光危害性成分测量,而且还用它探测扩散阻挡层裂口。