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This paper presents a method that embeds stability-sensitive filter in the temporal matching kernel with explicit feature maps (TE). The added filter improves the robustness of TE to noise for content-based video retrieval. Originally TE embeds temporal information of frame descriptors by using explicit feature mapping in a fixed length video vector by using a temporal invariant match kernel. TE matches...
Fingerprinting Localization Solutions (FPSs) enjoy huge popularity due to their good performance and minimal environment information requirement. Considered as a data-driven approach, many modern data analytics can be used to improve its performance. In this paper, we propose tow learning algorithms, namely a deep learning architecture for regression and Support Vector Machine (SVM) for classification,...
Most state-of-the-art graph kernels only take local graph properties into account, i.e., the kernel is computed with regard to properties of the neighborhood of vertices or other small substructures. On the other hand, kernels that do take global graph properties into account may not scale well to large graph databases. Here we propose to start exploring the spacebetween local and global graph kernels,...
Post-database searching is a key procedure for peptide spectrum matches (PSMs) in protein identification with mass spectrometry-based strategies. Although many machine learning-based approaches have been developed to improve the accuracy of peptide identification, the challenge remains for improvement due to the poor quality of data samples. CRanker has shown its effectiveness and efficiency in terms...
Gender recognition from facial images has become one of challenging research problem in computer vision, security, verbal-nonverbal communication and human computer interaction applications nowadays. Because facial images include many information such as gender, facial expressions, age, ethnic origin in computer-aided applications, the success rate of the gender recognition depends on quality of facial...
With he rapid development of the mobile Internet industry, information security based on trusted computing is also becoming increasingly serious. Considering that most of the existing research is based on the static security measure, and based on the server and PC side, a security operation environment measurement framework based on mobile terminal is proposed in this paper to alleviate the information...
With the development of algorithms and computer skills, deep learning using CNN (convolutional neural network) has been applied to various fields, especially in image processing field. In this paper, we designed an improved model based on ResNet with CNN structure, and learned the database. The Chaucer Database used in the experiment consisted of 824 Chinese characters among the Chinese characters...
Recently, the combination of classification systems with semi-supervised learning has attracted researchers in several fields. Usually, for tasks with high complexity such as handwriting based age prediction, individual systems, using one classifier associated with specific data features, cannot provide satisfactory performance. In this paper, we investigate the contribution of the Co-training approach,...
Location based services like localization in wireless network are drawing more and more attention in the recent years. According to published literatures, the fingerprint based method outperforms many other methods, where constructing an accurate fingerprint database is a new challenge. In this paper, we introduce a Bayesian regression model, Gaussian Process Regression(GPR) model to profile the signal...
This paper presents a comparison study of different similarity metrics used for RSSI fingerprint based indoor localization. These metrics are used for nearest neighbor search which is a crucial step in fingerprint localization system. Including Euclidean distance, Manhattan distance and Gauss distance, the present study compares the localization error respect to a proposed parameter named “error density”...
This paper evaluates a mechanism for applying machine learning (ML) to identify over-constrained IaaS virtual machines (VMs). Herein, over-constrained VMs are defined as those who are not given sufficient system resources to meet their workload specific objective functions. To validate our approach, a variety of workload-specific benchmarks inspired by common Infrastructure-as-a-Service (IaaS) cloud...
Visual or image-based self-localization refers to the recovery of a camera's position and orientation in the world based on the images it records. In this paper, we deal with the problem of self-localization using a sequence of images. This application is of interest in settings where GPS-based systems are unavailable or imprecise, such as indoors or in dense cities. Unlike typical approaches, we...
Alongside the fast development of new science and innovation, the elements of Smart gadgets like Smart Phones, Smart TV, smart watches smart home appliances, IoT devices etc. turn out to be increasingly powerful and are playing a basic part in the day today world. Operating systems like Android, iOS, Windows, Blackberry so on gives an operating environment for the Smart devices [1]. Android, a Linux...
Emerging non-volatile memory (NVM) technologies provide opportunities to improve the performance of key-value databases (KVDBs) by deploying database on NVM. However, existing in-memory KVDBs cannot fully exploit the advantages of NVM. They process data on in-memory database and store an image on persistent storage via an underlying file system. The performance of database operations is degraded by...
The present work proposes to recognize the static hand gestures taken under invariations features as scale, rotation, translation, illumination, noise and background. We use the alphabet of sign language of Peru (LSP). For this purpose, digital image processing techniques are used to eliminate or reduce noise, to improve the contrast under a variant illumination, to separate the hand from the background...
Neuroscience researchers have a keen interest in finding the connection between various brain regions of an organism. Researchers all across the globe are finding new connections everyday and it is very difficult to keep track of all those, so it is important to create a centralized system which is able to give the relation between brain entities. Databases like PubMed contains abstracts and references...
This paper presents the design of a convolutional neural network architecture using the MatConvNet library for MATLAB in order to achieve the recognition of 2 classes of hand gestures: ”open” and ”closed”. Six architectures were implemented to which their hyperparameters and depth were varied to observe their behavior through the validation error in the training and accuracy in the estimation of each...
Heart electrical activity is measured on the body surface; this measure is known as electrocardiogram (ECG). The ECG signals are commonly accompanied by different types of noise, that can lead to a difficult and imprecise computational process to diagnose heart diseases. In this paper, we propose the Kernel Principal Component Analysis (KPCA) method, usually used in image denoising, for minimizing...
In this paper, we propose a cost function that corresponds to the mean square errors between estimated values and true values of conditional probability in a discrete distribution. We then obtain the values that minimize the cost function. This minimization approach can be regarded as the direct estimation of likelihood ratios because the estimation of conditional probability can be regarded as the...
This paper attempts to represent the mapped data in the radial basis function (RBF) feature space under non-negativity constraints and develops a RBF kernel based non-negative matrix factorization (KNMF-RBF) algorithm. Based on an objective function with Frobenius norm, we obtain the multiplicative update rules of our KNMF-RBF approach using kernel theory and gradient descent method. The proposed...
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