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To improve the accuracy of fault diagnosis for motor bearing, an ensemble approach for fault diagnosis based on Ensemble Empirical Mode Decomposition (EEMD), Improved Gravitational Search Algorithm (GSA) and Incremental Probabilistic Neural Network (IPNN), called EEMD-IGSA-IPNN, is presented. Firstly, EEMD is used to extract the fault feature from the data of the motor bearing, then IGSA optimizes...
Human Computer Interaction (HCI) has been a popular research area during the last few years. Compared with the tradition HCI methods such as using a keyboard or mouse, people prefer to have their tasks done in a more natural way. As an essential form of non-verbal communication in daily life, gesture is a good choice to turn the ideas into reality. Although various recognition methods are proposed...
Query-by-Example Spoken Term Detection (QbE-STD) under low-resource settings, is the task of retrieval which can be done via the example of an audio. The searching phase involves highly computationally intensive Dynamic Time Warping (DTW)-based matching techniques. Search space reduction is an important need in order to reduce the space of searching and hence, reduce the computational complexity....
With the development of the Internet continues accelerating, network news has gradually become an indispensable source where people get news events. How to obtain the core news events from network news and grasp the dynamic information of the society has gradually become one of the problems that people concerned. This paper researched the features of network news and proposed an event detection algorithm...
In order to enhance efficiency and accuracy of dynamic hand gesture recognition based on HMM method. we propose a new HMM algorithm combined with the DTW for the computation's high complexity of HMM method in the training stage. The new HMM can establish the relationship of fuzzy closeness degree between the DTW algorithm and the HMM algorithm. Meanwhile, it can combine with the template adaptive...
With the increasing availability of spoken documents in different languages, there is a need of systems performing automatic and unsupervised search on audio streams, containing speech, in a document retrieval scenario. We are interested in retrieving information from multilingual speech data, from spoken documents such as broadcast news, video archives or even telephone conversations. The ultimate...
This paper proposes a solution that can be used to develop an assistive device to help people that have tracheostomies to make use of verbal communication. Based on the analysis of video images, we propose to develop a system suitable to be used to produce vowel sounds. Exploring the McGurk effect, we expect seeing the mouth movements and listening to the corresponding vowels to be sufficient for...
In the last few years, the number of mobile devices such as smartphones and tablets, in circulation, has increased dramatically. The primary and often only protection mechanism in these devices is authentication using a password or a Personal Identification Number (PIN). Passwords are notoriously known to be a weak authentication mechanism, no matter how complex the underlying format is. A more secure...
The smoke detection in remote video surveillance is of great importance in forest fire prevention since smoke usually appears before fire. In order to solve this problem, we proposed a novel smoke detection algorithm based on fast self-tuning background subtraction segmentation and judgments of smoke analysis. First, a self-tuning background algorithm is utilized on the source image to segment the...
This paper presents a methodology implementation of a turn-key training system for music (singing voice). The implementation took place with Max/Msp development software. Initially we create a small corpus of anthems for testing purposes by recording four(4) small hymns. Each hymn is been performed three(3) times from the same chanter. The reason of that repetition answers the purpose of finding the...
Anomaly detection technique play an extraordinary role in the Intrusion Detection System (IDS) for its ability to detect novel attacks. To overcome the high-dimensionality problem the anomaly detection cursed of, we propose a novel Meta-Heuristic-based Sequential Forward Selection (MH_SFS) feature selection algorithm, which can be generally implemented in anomaly detection system. It is an improvement...
The paper proposes a dynamic shape context retrieval algorithm based on statistic. It selects shape's feature point's number dynamically, and statistics the number of target shape's feature points in different area block to form a contour feature point histogram. Finally, measuring the similarity is used dynamic programming algorithm. This method can selects the number of feature points adaptively,...
Online human action recognition has broad application prospect in many fields of computer vision. Simultaneously, with the advent of depth camera, it brings on a new trend of online human action recognition but still present some unique challenges. In this paper, to solve the lower accuracy of the existing online human action recognition algorithm based on depth camera, we adopt the improved Dynamic...
With the massive changes in input acquisition systems such as smart phones and tablets, the field of handwriting recognition has more attention accorded by a several researchers. This article addresses the problem of online Arabic character segmentation. Our approach is based on top-down segmentation-free of Arabic character by detecting the candidate points in the general chain code of the character...
This paper studies the content-based music retrieval and the methods for main modules. It improves the defect of DTW algorithm, which needs longer running time for melody matching, and proposes a DTW melody matching algorithm based on numerical index. It first establishes numerical index according to pitch difference information in the melody feature library. Then it performs rough matching based...
Iris Recognition (IR) is a demanding field, owing to varying contrast and live-tissues. The important contrast invariant features need to be extracted to address this problem. This paper proposes a novel feature selection evolutionary algorithm, namely, Dynamic Binary Particle Swarm Optimization (DBPSO) for enhanced IR. DBPSO generates a highly optimized global best vector, using which, the number...
Intrusion behavior and detection analysis particularly rely upon the type of data. Most of the datasets used in intrusion analysis are heterogeneous and imbalanced data sets. In these data sets, the features vary with a huge difference in between and within the feature values. This is very effective while taking decision, especially in the supervised learning. To analyze the intrusion problem, support...
The aim of this work is to design a SLAM algorithm for localization and mapping of aerial platform for ocean observation. The aim is to determine the direction of travel, given that the aerial platform flies over the water surface and in an environment with few static features and dynamic background. This approach is inspired by the bird techniques which use landmarks as navigation direction. In this...
Extracting opinion words and opinion targets from online reviews is an important task for fine-grained opinion mining. Usually, traditional extraction methods under the pipeline-based framework have higher precision but lower recall, while methods in the propagation-based framework possess greater recall but poorer precision. To achieve better performance both in precision and recall, this paper proposes...
For any real-time application, detection and tracking of features becomes very important. The detection and tracking algorithms have to be very robust and efficient with least or zero false positives and false negatives. We use a novel combination for detection and tracking purpose. In this paper we propose a robust mouth region extraction and tracking algorithm that works in real-time. The region...
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