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Speaker diarization systems aim to segment an audio signal into homogeneous sections with only one active speaker and answer the question "who spoke when?" We present a novel approach to speaker diarization exploiting spatial information through robust statistical modeling of Time Difference of Arrival (TDOA) estimates obtained using pairs of microphones. The TDOAs are modeled with Gaussian...
This paper describes the use of Unmanned Aerial Vehicle (UAV) technology to fight apple scab. Specifically, it shows how it is possible to improve the scab risk evaluation basing on the actual apple leaves development status, yielded from UAV images, as input to the infection model. For this purpose, we introduce a new index, called Leaf Development Index (LDI), which is evaluated during the main...
With the development of social media technology, users often register accounts, post messages and create friend links on several different platforms. Performing user identity mapping on multi-platform based on the behavior patterns of users is considerable for network supervision and personalization service. The existing methods focus on utilizing either text information or structure information alone...
Recognition of satirical language in social multimedia outlets turn out to be a trending research area in computational linguistics. Many researchers have analyzed satirical language from various point of views: lexically, syntactically, and semantically. However, due to the ironic dimension of emotion embedded in satirical language, emotional study of satirical language has ever left behind. In this...
Loop closure detection is very important in visual simultaneous and localization and mapping system (SLAM), which can reduce the accumulated drift. The most successful methods are based on Bag-of-Words model and need a large visual word dictionary. Recently, the VLAD, the state-of-the art compact descriptor, has achieved a great success in large scale image retrieval. In this paper, a novel vlad-based...
As people are spending more time to shop and view reviews on line, some reviewer write fake reviews to earn credit and to promote (demote) the sales of product and stores. Detecting fake reviews and spammers becomes more important when the spamming behavior is becoming damaging. This paper proposes three types of new features which include review density, semantic and emotion and gives the model and...
Historical user activity is the key for building user profiles to predict the user behavior and affinities in many web applications such as targeting of online advertising and social recommendations. In these scenarios, the items recommended to users must match their profiles. However, user profiles are temporal, so, changes in a user's activity patterns are particularly useful for improved prediction...
In this paper, we propose a feature representation that achieves translation, rotation, and scale invariant simultaneously. We first proposed a novel component, called Block Based Integral Image, to search the densest region of feature points. This aims to find the center of potential object in the image. Then, with the improved object center, we apply Spatial Pyramid Ring (SPR) by to handle translation...
System Testing is a key technology of CVIS (Cooperative Vehicle Infrastructure System). A shortest test sequence generating approach in CVIS is proposed in this paper. The paper firstly analyzes the spatial-temporal state of vehicle and complexity of infrastructure in network. Then paper designs system features and test cases, and introduces the concept of support index of the test case to system...
Feature location is a program comprehension activity in which a developer inspects source code to locate the classes or methods that implement a feature of interest. Many feature location techniques (FLTs) are based on text retrieval models, and in such FLTs it is typical for the models to be trained on source code snapshots. However, source code evolution leads to model obsolescence and thus to the...
In this paper we describe a behavioral state classifier employing a three-factor node reliability measure based upon inferred Ability, Integrity, and Benevolence (AIB) to assess node reliability. In contrast to typical scalar measures, this multi-metric index creates a reliability space that is more descriptive and in which distinctions can be drawn between node behaviors ranging from small deviations...
This paper proposes a technique to recognize the emotion present in the speech signal using Continuous Density HMM.The Perceptual Linear Predictive Cepstrum (PLPC) and Mel Frequency Perceptual Linear Predictive Cepstrum (MFPLPC) features are considered in our work and they are extracted from the speech and training models are created using Continuous Density HMM. For the Speaker Independent classification...
Standard deep neural network-based acoustic models for automatic speech recognition (ASR) rely on hand-engineered input features, typically log-mel filterbank magnitudes. In this paper, we describe a convolutional neural network - deep neural network (CNN-DNN) acoustic model which takes raw multichannel waveforms as input, i.e. without any preceding feature extraction, and learns a similar feature...
In academic domain, technical conferences are conducted to share different research ideas and to propose new research methodologies. The number of conferences being conducted in different academic domains and the number of research participants in conference are increasing rapidly. The conference chairs face difficulty in assigning panel of reviewers for various research topics. A ranked list of experts...
Accurate measurement of the mill level is a key factor to improve the ball mill's productive efficiency, safety and economy. Aiming at solving the critical problem of the mill level soft sensor, feature extraction of the processing parameters, a novel method based on Deep Belief Network (DBN) is proposed. DBN is one of the deep learning methods, which focuses on learning deep hierarchical models of...
To achieve enhanced image recognition, it is necessary to accurately extract the contour of the recognition target from the input image in a preprocessing step. Contour extraction methods based on the active contour model(Snakes) require the operator to specify the parameter values that best catch the shape of the target. However, it is difficult to guess the parameter values since the relationship...
In the present study we investigate the evolutionary feature subset selection using wrapper based genetic algorithms on Multi-temporal datasets. Feature subset selection helps in reducing the original feature dimension and also yields high performance. The evolutionary strategy attains a global optimum by reducing the computations iteratively and by traversing intelligently in the entire feature space...
For natural image segmentation, due to features from a single image are hard to describe the complex scene information, this paper presents a new method based on the fusion model evaluation index PRI to fuse color histogram features in 3 color spaces, RGB, XYZ, LUV, and texture features. We experiment on images from Berkeley segmentation databases and compare the quantitative and qualitative experimental...
The spinal cord is a vital organ that serves as the only communication link between the brain and the various parts of the body. It is vulnerable to traumatic spinal cord injury and various diseases such as tumors, infections, inflammatory diseases and degenerative diseases. The exact segmentation and localization of the spinal cord are essential to effective clinical management of such conditions...
In this paper, we present a novel 3D model alignment method by analyzing the voxels of 3D meshes and a visual similarity based 3D model matching and retrieving method using active tabu search. Firstly, each 3D model is voxelized and applied voxels based PCA transformation, then it is represented by six depth images which are projected by rendering in the PCA coordinate system. Hybrid descriptors are...
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