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The back-end database is pivotal to the storage of the massive size of big data Internet exchanges stemming from cloud-hosted web applications to Internet of Things (IoT) smart devices. Structured Query Language (SQL) Injection Attack (SQLIA) remains an intruder's exploit of choice on vulnerable web applications to pilfer confidential data from the database with potentially damaging consequences....
The presence of struck-out text in handwritten manuscripts may affect the accuracy of automated writer identification. This paper presents a study on such effects of struck-out text. Here we consider offline English and Bengali handwritten document images. At first, the struck-out texts are detected using a hybrid classifier of a CNN (Convolutional Neural Network) and an SVM (Support Vector Machine)...
Local binary pattern (LBP) has limitation in extracting the edge and direction information, which is vital to infrared face recognition. A new infrared face recognition algorithm fusion of LBP and histogram of oriented gradients (HOG) is proposed. First, LBP operator is adopted to extract the texture feature of an infrared face, and then the edge features of the original infrared face are extracted...
Recently, deep features extracted from Convolutional Neural Networks (CNNs) have been widely adopted in various applications, such as face recognition. Compared with the handcrafted descriptors, deep features have more powerful representation ability which can lead to better performance. Effective feature representations play an important role in ear recognition. While deep features have not been...
The monitoring of volumetric changes in the brain during neurological diseases is done with three dimensional structural MR images. Numerical methods are needed to evaluate the volumetric difference between healthy and diseased MR image groups. Voxel based morphometry is a numerical method used to perform inter-group and intra-group analysis of MR images. With this method, the volume differences between...
In education system, students' feedback is important to measure the quality of teaching. Students' feedback can be analyzed using lexicon based approach to identify the students' positive or negative attitude. In most of the existing teaching evaluation system, the intensifier words and blind negation words are not considered. The level of opinion result isn't displayed: whether positive or negative...
Facial Expression Recognition performs a primary role Human computer interaction (HCI) field. The author proposed hybrid approach which performed better in recognizing facial expression. In the paper, the emotions are detected by calculating the feature vector of the input facial image using Hybrid approach and distinguish or classify the features using SVM classifier. The performance of recognition...
Parkinson's disease (PD) is a neurological disorder associated with a progressive decline in motor skills, speech, and cognitive processes. Since the diagnosis of Parkinson's disease is difficult, researchers have worked to develop a support tool based on algorithms to separate healthy controls from PD patients. Online handwriting analysis is one of the methods that can be used to diagnose PD. The...
The recognition of Arabic writing is still an important challenge due to its cursive nature and high topological variability. Traditional machine-learning techniques required careful engineering and considerable domain expertise to transform raw data into a feature vector from which the classifier could classify the input pattern. In recent years, deep learning approach has acquired a reputation for...
The Aim of the proposed paper is to recognize offline Hand written Telugu characters using Optical character recognition, OCR is one of the most popular and challenging topic of pattern recognition This paper proposes an OCR system for Telugu documents which comprises of three stages, namely pre-processing, feature extraction, and classification. In the preprocessing stage, we have employed median...
In this paper, a system based on support vector machines is proposed for content-based dialect classification and retrieval. This work is part of an ongoing effort to address the needs of new under-resourced languages. The recognition system will work for the interest and welfare of the Pashto speaking people and will help in keeping the language dialects alive by this process. Voice samples are collected...
Human Activity detection is an imperative area of research in computer vision. This paper focuses on activity recognition by construction personnel at the construction sites. The method uses bag of features (BOF) approach to detect an activity. Here we have considered five types of activities done at construction sites namely ladder climbing, brick laying, carpentry work, painting and plastering work...
After “9.11” terrorist attacks, more advanced information technologies have been developed to counter terrorism domain to enhance the performance of early warning system. Machine learning based data mining can be applied to predict terrorist event hidden in terrorist attack events and by which the experts expect to get a clear picture of what the terrorists are thinking about in order to step up defense...
This paper explores the significance of phase information for speech emotion classification. The phase information is extracted from the discrete Fourier transform (DFT) spectrum. The phase of the pitch harmonic is used as a proposed feature for speech emotion classification. Pitch frequency varies with emotions, and due to this pitch harmonic also varies with different emotions. It is expected that...
Scene classification is an extremely challenging task owing to the complexity of the scene content. In this paper, a novel method is designed to harvest the discriminative representation for the scene classification. The proposed model simultaneously takes both discriminative patches and entire scene image into consideration. First, the discriminative patches are extracted from the raw scene image...
In this paper, we propose to achieve the classification of pathologic voices and essentially the classification between organic pathologies: it's about polyp, edema and nodule pathologies using new features. The principle contribution in this work is to provide new parameter more efficient than the classic MFCC. It's about calculating MFCC not from the speech signal but from the speech multiscale...
Speech uttered by the human beings contains the information about speakers, languages and contents. Language of uttered speech can easily be identified by extracting the language specific information from it. Identification of language of speech is known as Language Identification (LID). Identification of language from speech is helpful in its translation, speech recognition and speech activated automatic...
Accurate segmentation of retinal vessel plays an important role in the computer-aided diagnosis of eye diseases. Existing supervised methods extract features only from green channel due to its much higher contrast between vessel and background than in red and blue channels. However, red and blue channels also contain useful information for distinguishing vessel from background. This work investigates...
The performance of a speaker verification system is severely degraded by spoofing attacks generated from artificial speech synthesizers. Recently, several approaches have been proposed for classifying natural and synthetic speech (spoof detection) which can be used in conjunction with a speaker verification system. In this paper, we attempt to develop a joint modelling approach which can detect the...
Continuous prediction of dimensional emotions (e.g. arousal and valence) has attracted increasing research interest recently. When processing emotional speech signals, phonetic features have been rarely used due to the assumption that phonetic variability is a confounding factor that degrades emotion recognition/prediction performance. In this paper, instead of eliminating phonetic variability, we...
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