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Based on the kernel method and graph theory, this paper proposes a novel Kernel Non-negative Matrix Factorization with Local and Non-local feature (LN-KNMF) approach for face recognition. We establish the objective function in kernel space which incorporates two scatter quantities, namely local scatter and non-local scatter. They are determined by the local adjacent graph matrix and non-local adjacent...
We consider the problem of ligand affinity prediction as a regression task, typically with few labelled examples, many unlabelled instances, and multiple views on the data. In chemoinformatics, the prediction of binding affinities for protein ligands is an important but also challenging task. As protein-ligand bonds trigger biochemical reactions, their characterisation is a crucial step in the process...
Recently deep Convolutional Neural Networks have been successfully applied in many computer vision tasks and achieved promising results. So some works have introduced the deep learning into face anti-spoofing. However, most approaches just use the final fully-connected layer to distinguish the real and fake faces. Inspired by the idea of each convolutional kernel can be regarded as a part filter,...
In many computer vision systems, one object can be described by multi-view data. Compared with individual view, multi-view data can contain complete and complementary information of the problem. But when views capture information which is uniquely but not complete enough to give an uniform learning performance, multi-view data may degrade the learning performance and it is therefore not an ideal solution...
Several applications in numerical scientific computing process sparse matrices with either a regular or irregular structure. The very large size of these matrices requires to use compressing formats and target parallel/distributed architectures in order to reduce both space complexity and processing time. The optimal compression format (OCF) of such matrices may in fact vary according to both the...
In this paper, the proposed implementation of a soft-biometric system for automatic age detection from facial images is described. In order to do this, the method followed was that of a classical biometric system. The first step is preprocessing, to enhance the feature extraction. The next step is the parameterization, where techniques like wavelet transformed, discrete cosine transformed or local...
Ground Penetrating Radar (GPR) is used for subsurface exploration across different applications like landmines detection. It can detect and deliver the response of any buried kinds of object, however it cannot discriminate between landmines and false alarms. In this paper, we propose a detection method based on support vector machine (SVM) using one-dimensional GPR delivered data called Ascans. Each...
Non-negative Matrix Factorization (NMF) has been widely studied and applied to variant computer vision tasks, such as image clustering and pattern classification. Meanwhile, real world stimuli for human neural system (e.g., face images) are usually represented as high-dimensional data vectors rely on graph embedding in original Euclidean space. Thus, the traditional NMF and its variants exhibit weakness...
Building secure systems used to mean ensuring a secure perimeter, but that is no longer the case. Today's systems are ill-equipped to deal with attackers that are able to pierce perimeter defenses. Data provenance is a critical technology in building resilient systems that will allow systems to recover from attackers that manage to overcome the "hard-shell" defenses. In this paper, we provide...
This paper proposes a new approach for image classification by combining pyramid match kernel(PMK) with spatial pyramid. Unlike the conventional spatial pyramid matching (SPM) approach which only uses a single-resolution feature vector to represent an image, we use a multi-resolution feature vector to represent an image for SPM. We then calculate the match scores at each resolution of SPM representation...
Handwriting has been known to be a very strong identifying characteristic of an individual and can be considered a behavioural biometric trait. This has made hand writer identification an important area of research. In this paper, a novel offline writer identification system is proposed using ensemble of multi-scale local ternary pattern histogram features. Features are extracted at multiple scales...
This paper addresses the problem of automatic target recognition (ATR) using inverse synthetic aperture radar (ISAR) images. In this context, we propose a novel approach for feature extraction to describe precisely an aircraft target from ISAR images. In our approach, a visual attention model is adopted to separate the salient regions from the background. After that, the scale invariant feature transform...
Recently, the indoor positioning system (IPS) based on received signal strength (RSS) has received great attention in both industry and academic fields due to the ubiquity of wireless local area networks (WLAN). In general, Wi-Fi signal is suffering from two major limitations: first, the signal suffers from variation overtime. Secondly, the signal distribution recording on some devices can be more...
This paper proposes a new Utterance Verification (UV) algorithm based on i-vector. Phone segments are extracted and concatenated from the training data, which are used to train the Universal Background Model (UBM) and the Total Variability (TV) matrix, and then, i-vector is extracted from the enrollment and evaluation data using UBM and TV matrix. We compare two Confidence Measures (CMs), cosine distance...
Visual localization is the process of finding the location of a camera from the appearance of the images it captures. In this work, we propose an observation model that allows the use of images for particle filter localization. To achieve this, we exploit the capabilities of Gaussian Processes to calculate the likelihood of the observation for any given pose, in contrast to methods which restrict...
In recent years, we can observe an increasing use of biometric technology in our daily lives. Face recognition has several advantages over other biometric modalities, since that it is natural, nonintrusive, and it is a task that humans perform routinely and effortlessly. Following a recent trend in this research field, this paper focuses on a part-based face recognition, exploring and evaluating specific...
Eye detection is a front end problem to be solved efficiently by face detection and human surveillance systems. Features such as accuracy and computational cost are to be considered for a successful approach. We describe an integrated approach that takes the ROIs outputted by a Viola and Jones detector, constructs HOGs features on those and learn an special function to mapping these features to a...
This paper presents a new flexible approach to predict the gender of the writers from their handwriting samples. Handwriting features can be extracted from different methods. Therefore, the multi-feature sets are irrelevant and redundant. The conflict of the features exists in the sets, which affects the accuracy of classification and the computing cost. This paper proposes a Mutual Information (MI)...
In this paper, we propose two novel textural-based features for writer identification: CoHinge and QuadHinge which are based on the spatial and attribute co-occurrence of the Hinge kernel. The CoHinge feature is the joint distribution of the Hinge kernel on two different pixels of writing contours and the QuadHinge feature is the joint distribution of angles and curvature information of contour fragments...
Whole-system data provenance provides deep insight into the processing of data on a system, including detecting data integrity attacks. The downside to systems that collect whole-system data provenance is the sheer volume of data that is generated under many heavy workloads. In order to make provenance metadata useful, it must be stored somewhere where it can be queried. This problem becomes even...
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