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58 articles for “Discriminant analysis”
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A Robust Face Recognition Model based on Convolutional Neural Networks
Abstract: From the past several years, face recognition is one of the challenging issues in computer vision, due to three main technical problems in it. 1) Expression problem: in which same person shows more than one expression. 2) Illumination problem: in which face images of the person are strongly corrupted by lightning and 3) poses problem: in which large portion of the face becomes invisible due to occlusion. To this end …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 1, 2018 · pp. 1–11 Read article
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Robust Quadratic Discriminant Rule using Comedian
Abstract: Discriminant analysis aims to get rules that separate the groups of observations. Moreover, it can be used to classify new observations into one of the known groups. The classical discriminant techniques are based on the classical estimates of mean vector and variance covariance matrix. Unfortunately, these classical estimates are highly influenced by the extreme observations and hence any analysis based on these estimates will provide misleading results when the data …
Published in Research & Reviews : Journal of Statistics · Vol. 8, Issue 2, 2019 · pp. 41–47 Read article
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Dimensionality Reduction using Eigenfaces and Fisherfaces for Face Recognition Applications using Kernel LMS Algorithm
Abstract: AbstractFace recognition is an intricate numerical technology in computer systems that can support recognition of human faces using methods such as principal component analysis (PCA), linear discriminant analysis (LDA), etc. by comparing the given facial uniqueness with the already available face database. PCA and LDA are classical feature extraction and data representation techniques used in face recognition algorithm involving unsupervised statistical methods. The 2-D facial image can be transformed into …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 2, 2015 · pp. 29–55 Read article
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Computer-aided Drug Design Method for Anti-hepatitis C Drug Design
Abstract: Hepatitis C is a disease caused by the hepatitis C virus and can cause serious liver damage. There is currently no vaccine for this disease and the number of infections continues to increase worldwide. Currently used antiviral drugs are interferon alfa-2a and ribavirin, but about half of patients do not respond to therapy. Therefore, new drugs that protect against hepatitis C need to be investigated. Computational drug methods have been …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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A New Evaluation Index for Application of Machine Learning Algorithms to Determine Trust in Skewed Social Media Data
Abstract: In this paper we study the problem of accuracy paradox which arises on the application of machine learning algorithms for inference of trust in skewed social media data. Skewness is defined as the under representation of one class over another in a binary classification problem. We achieved our purpose of identifying the accuracy paradox problem in various algorithms by identifying a new evaluation index called predictive index. The dataset used …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 3, 2018 · pp. 49–57 Read article
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A Survey on Face Recognition Techniques and Its Applications
Abstract: Face recognition has been a fast growing, and interesting area in real time applications. Automatic face recognition has shown great achievement for high-quality images under embarrassed conditions; for video-based recognition it is hard to achieve similar levels of performance. Human face detection and tracking of moving objects in the video are important tasks of the computer vision. Human and object frames are separated by implementing a face detection algorithm for …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 3, 2014 · pp. 16–21 Read article
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Review Paper on Efficient Quality Inspection of Food Products Using Neural Network Classification
Abstract: AbstractWith the increasing competiveness in the field of food production growing at a faster pace across the globe, quality is one of the most desirable features that a product should possess. The ability to produce quality as well as safety food is the most prerequisite factors for both, national and international market. This paper explains the recently developed approaches and latest research efforts related to the assessment of the quality …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 4, Issue 1, 2017 · pp. 1–14 Read article
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Face Recognition using LDA based Support Vector Machine
Abstract: AbstractRecognition of a person is an easy task for human brains. From different experiments, we have found that even one to three days old babies are able to distinguish between known faces. So, it is very difficult task for a computer to recognize an unknown human face although a computer has been trained with a huge set of human face. Now-a-days face recognition has received significant attention of researchers. Lots …
Published in Journal of Computer Technology & Applications · Vol. 5, Issue 2, 2014 · pp. 1–7 Read article
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Improved Face Recognition Rate Based on PCA and LDA Using Image Preprocessing Techniques
Abstract: Principal component analysis (PCA) and linear discriminant analysis (LDA) are two powerful tools utilized for dimensionality reduction and feature extraction in most of pattern recognition applications. PCA selects features important for class representation while LDA algorithm selects features that are most effective for class separability. This paper carries out a comparative study of the two important algorithms in the context of enhancement obtained using certain image preprocessing techniques. The implementation …
Published in Journal of Instrumentation Technology & Innovations · Vol. 5, Issue 2, 2015 · pp. 19–24 Read article
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Back-Propagation Neural Network Based Speaker Identification Under Noise Distortion
Abstract: The aim of this paper is to evaluate the performance of the proposed speaker identification system where Wiener filtering technique has been used to eliminate the background white Gaussian noises and linear discriminant analysis has been used to reduce the dimension of the speech features. Since the audio signal captures more environmental noises than other biometrics modalities, the main emphasis of this paper is to analyze the problem domains of …
Published in Trends in Electrical Engineering · Vol. 5, Issue 2, 2015 · pp. 1–6 Read article
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Discrete Hidden Markov Model based Face Recognition System Introducing Sustainability of Uneven Lighting Distortion
Abstract: The aim of this work is to enhance the performance of appearance based face recognition system to remove the uneven lighting effect which is generally occurred in natural environment. Active Shape Model has been used to detect the facial shape and contrast based edge detection technique has been applied to reduce the uneven lighting problem. Linear Discriminant Analysis has been used to reduce the dimension of the facial feature vector. …
Published in Trends in Electrical Engineering · Vol. 4, Issue 1, 2014 · pp. 9–16 Read article
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Alzheimer disorders diagnosis system design using machine learning for EEG signal
Abstract: The diagnosis of Alzheimer's disorders (AD), a prevalent neurological disorder, can created by utilising a range of therapeutic methods, including the electroencephalogram (EEG), which has been especially successful in the past. The objective for this study is to develop a computer-aided diagnosis tool which may recognize AD from EEG data. The EEG information was cleaned up with a band-pass elliptic digital filter to remove any interference or disruptions. The filtered …
Published in Journal of Control & Instrumentation Read article
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Dimensionality Reduction: A Brief Survey on Its Myriad Techniques
Abstract: This paper is a short survey and analysis on different techniques and methods using which efficiency of existing techniques can be improved which are used for data exploration, or search for those features which has deeper relationship amongst the variable, which relies on greater extent on visual methods. However, for multidimensional data set with real time data collected captured using sensors or real time applications, redundant and unused or wanted …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 6, Issue 2, 2017 · pp. 46–51 Read article
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Evaluation Algorithm for Discrimination between Fault and Power Swing Using Independent Component Analysis
Abstract: The analysis of faults and disturbances in power systems is a basic requirement for a secure and reliable electrical power supply. Independent component analysis (ICA) is an efficient computational method used to find out hidden components in a set of sampled data. The basic target of ICA is to find a linear representation and relation between nongaussian data captured during disturbance, so that the components are statistically independent, or as …
Published in Journal of Power Electronics and Power Systems · Vol. 6, Issue 3, 2016 · pp. 53–59 Read article
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Bank Loan Prediction by using Logistic Regression
Abstract: In the modern era of science and technology, the banking sector is also growing very fast and a lot of people are applying for bank loans. But the bank has limited assets and can be granted to limited number of people only, so the bank must ensure that the person whom the loan is granted is eligible enough to pay it back. So, in this study, we will try to …
Published in E-Commerce for Future & Trends · Vol. 8, Issue 2, 2021 · pp. 17–21 Read article
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A Review of Code Defect Likelihood Using ML Methods
Abstract: AbstractSoftware begets defects and defects are inevitable in software design and coding. This paper focused on five machine learning analysis models (MLAM); Support Vector Machine, Random Forest, K-Nearest Neighbor, Classification and Regression Tree, and Linear Discriminant Analysis. These models are trained to detect software defects using the software defect dataset from Promise data repository. The collected dataset is preprocessed to reduce the amount of redundant features using a dimension reduction …
Published in Journal of Open Source Developments · Vol. 7, Issue 3, 2020 · pp. 1–6 Read article
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A Novel Approach of Gait Recognition Using LDA, PAL and Neural Network Technique
Abstract: Gait recognition is one type of biometric technology that can be used to the monitor person without their any cooperation. Controlled atmospheres for example; military installations, banks and even airports required to be able to rapidly detect threats and give differing stages of access to various customer groups. Gait presents a specific way or moving manner on the foot and gait recognition is the recognizing procedure an individual through the …
Published in Recent Trends in Parallel Computing · Vol. 2, Issue 3, 2015 · pp. 27–35 Read article
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Dimensionality Reduction Techniques and their Applications in Cancer Classification: A Comprehensive Review
Abstract: Dimensionality reduction techniques have become a vital tool in the investigation of high-dimensional data like gene expression profiles in cancer research. Here is a review, we deliver a comprehensive overview of dimensionality reduction techniques and their applications in cancer classification. Firstly, we introduce the concepts and approaches of dimensionality reduction, and after that, we explore several methods for decreasing dimensionality. These techniques include Linear Discriminant Analysis (LDA), Principal Component Analysis …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 1, Issue 2, 2023 · pp. 35–45 Read article
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Computer Aided Diagnosis of Breast Cancer using Machine Learning Techniques
Abstract: Breast cancer is one of the significant health problems that lead to early mortality in women, especially those between 40 and 55 years of age all over the world. In recent years, the number of breast cancer cases among women has risen significantly, making early and accurate diagnosis more important than ever. Computer-aided diagnostic (CAD) tools have become valuable in supporting radiologists by enhancing the precision of breast cancer detection. …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 2, 2025 · pp. 1–11 Read article
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Alzheimer disorders diagnosis system design using machine learning for EEG signal
Abstract: The diagnosis of Alzheimer's disorders (AD), a prevalent neurological disorder, can created by utilising a range of therapeutic methods, including the electroencephalogram (EEG), which has been especially successful in the past. The objective for this study is to develop a computer-aided diagnosis tool which may recognize AD from EEG data. The EEG information was cleaned up with a band-pass elliptic digital filter to remove any interference or disruptions. The filtered …
Published in Journal of Control & Instrumentation · Vol. 14, Issue 1, 2023 · pp. 9–22 Read article