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As the size of digitized painting collections increase, it becomes more difficult to organize and retrieve paintings from these collections. To manage search and other similar operations efficiently, it becomes necessary to organize the painting databases into classes and sub-classes. Manual tagging of these ever-increasing databases would become very costly and time consuming. The above challenging...
This work is mainly intended at identifying emotion contribution of different vowels in Telugu language. Instead of processing the entire speech signal we propose to focus only vowel parts of the utterance (/a/, /i/, /u/, /e/ and /o/). By analysing the vowels we can discriminate the emotions. In this work spectral and prosodic features are used for studying the effect of emotions on different vowels...
Biometric identification verifies user identity by comparing an encoded value with a stored value of the concerned biometric characteristic. Multimodal person authentication system is more effective and more challenging. The fusion of multiple biometric traits helps to minimize the system error rate. The benefit of energy compaction of transforms in higher coefficients is taken here to reduce the...
In this paper, we present a novel approach for recognition of human faces using Markov Random Fields (MRF) and Bayesian models. We examine the relationship between feature vectors in a close proximity system. The feature vectors are coefficients of the 2D Gabor Wavelet Transform (DWGT). The MRF is implemented to match the constraint configurations between the feature vectors. The MRFs posterior probability...
This paper tackles the problem of categorizing materials and textures by exploiting the second order statistics. To this end, we introduce the Extrinsic Vector of Locally Aggregated Descriptors (E-VLAD), a method to combine local and structured descriptors into a unified vector representation where each local descriptor is a Covariance Descriptor (CovD). In doing so, we make use of an accelerated...
We present a simple and effective means for position estimation designed to be deployed in urban and dense multipath environments characteristic of 4G wireless networks. To address the multipath channel of such environments a fingerprinting scheme is proposed. One of the drawbacks to this class of methods is the large initial cost associated with establishing a database matrix. This issue is addressed...
An example-based dialog model often require a lot of data collections to achieve a good performance. However, when it comes on handling an out of vocabulary (OOV) database queries, this approach resulting in weakness and inadequate handling of interactions between words in the sentence. In this work, we try to overcome this problem by utilizing recursive neural network paraphrase identification to...
Serious arrhythmic events in most of patients suffering from sudden cardiac arrest are Ventricular Fibrillation (VF) and Ventricular Tachycardia (VT). For these serious arrhythmic events, the timely employment of an electrical defibrillator may lead to successful results. From this viewpoint, widespread deployment of Automated External Defibrillators (AEDs) has been suggested and the most important...
In this paper, we consider the adaptation of two Partial Differential Equations (PDEs) on weighted graphs, p-Laplacian and eikonal equations, for semi-supervised classification tasks. These equations are a discrete analogue of well known geometric PDEs, which are widely used in image processing. While the p-Laplacian on graphs was intensively used in data classification, few works relate to the eikonal...
The popular i-vector approach to speaker recognition represents a speech segment as an i-vector in a low-dimensional space. It is well known that i-vectors involve both speaker and session variances, and therefore additional discriminative approaches are required to extract speaker information from the ‘total variance’ space. Among various methods, the probabilistic linear discriminant analysis (PLDA)...
Intrinsic variation is one of the major factors that aggravate performance of speaker verification system dramatically. In this paper, we focus on alleviating influence caused by intrinsic variation using sparse representation. Because the over-complete dictionary increases the flexibility and the ability to adapt to variable data in signal representation, we expect redundancy of the dictionary could...
The Domain Name System (DNS) is an essential component of the Internet infrastructure that translates domain names into IP addresses. Recent incidents verify the enormous damage of malicious activities utilizing DNS. Therefore, detecting malicious domains using the DNS network structure is an important challenge. We take the famous colloquial expression Tell me who your friends are and I will tell...
The appearance of the face varies drastically when background and pose change. Variations in these conditions make Face Recognition (FR) an even more challenging and difficult task. In this paper we propose two novel techniques, viz., Gabor-Feature-based DFT Shifting (GFDS) and Skin-detection-based Background Removal, to improve the performance of the FR system. GFDS is used to detect and neutralize...
Holistic approaches of face recognition are not robust to illumination, scale, occlusion and age variations. Various studies indicate that the performance of holistic approaches degrades as the face database size increases. In this paper, we propose a user specific landmark geometry based approach that assigns weights to different geometrical distances according to their role in face recognition process...
The goal of this paper is to present a critical comparison of existing classical techniques on recognition of human faces. This paper describes the four major classical face recognition techniques i.e., i) Principal Component Analysis (PCA), ii) Linear Discriminant Analysis (LDA), iii) Discrete Cosine Transform (DCT), and iv) Independent Component Analysis (ICA). Strong and weak features of these...
This paper presents a new method for texture based image retrieval. The proposed algorithm uses a periodically extended variant of the curvelet transform. The sum of the absolute value of differences in the mean and standard deviation between curvelet wedges representing the query image and the test image is used as the distance index. Performance improvement is demonstrated using the CUReT database,...
Local Binary Pattern (LBP) has been widely used for analyzing local texture features of an image. Several new extensions of LBP based texture descriptors have been proposed, focusing on improving the robustness to noise by using different encoding or thresholding schemes where the most widely known are Median Binary Patterns (MBP), Fuzzy LBP (FLBP), Local Quantized Patterns (LQP), and Shift LBP (SLBP)...
In recent years, information is increasing exponentially which makes it more and more difficult for people to find the needed information from the huge database. To fulfill this demanding, a high accurate and fast-time document retrieval algorithm is highly required for current applications. In this paper, based on the document similarity maximum criterion, we propose a new fast-time document retrieval...
In this paper, a simple biometric scheme based on RGB retinal fundus images is proposed. First, prominent vasculature energy based feature vectors are constructed from RGB retinal fundus images to utilize the unique pattern of retinal vasculature. Next, fast normalized cross-correlation based feature matching is employed for person identification on publicly available DRIVE and STARE databases. This...
Now-a-days, online interpersonal communications have become more preferable than face-to-face interactions. However, emotions play a significant role in online communication. Automatic extraction of emotions from the text is a hot research issue because it minimizes the communication gap and misunderstanding between users. To become emotionally more intelligent, our previous text to emotion analyzing...
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