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456 articles for “Features extraction”
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Machine Learning-Based Structure–Property Quantification of Advanced Polymer Composites
Abstract: Advanced polymer composites are widely used in high-performance engineering due to their superior mechanical and multifunctional properties. Accurate structure–property quantification is essential for efficient material design and reducing experimental costs. Existing Machine Learning (ML) approaches often exhibit limited predictive generalization due to inadequate feature discrimination and suboptimal hyperparameter tuning. To address these limitations, the proposed method enhances the ability to capture the complex nonlinear interactions among composite structural descriptors. The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Sustainable and Smart Solutions Utilizing Feature Descriptors Analysis
Abstract: Neighborhood highlight locators and descriptors (hereinafter extractors) play a key part within the cutting-edge computer vision for developing smart solutions. Their scope is to extricate, from any picture, a set of discriminative designs (hereinafter key points) show on a few parts of foundation and/or closer view components of the picture itself. A prerequisite of a wide run of down to earth applications (e.g., vehicle following, individual re-identification) is the plan …
Published in Journal of Electronic Design Technology · Vol. 13, Issue 3, 2022 · pp. 35–40 Read article
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Rotation Invariant Copy-Move Image Forgery Detection Using a Method Based on Fuzzy-Zernike Moments
Abstract: AbstractWithout leaving any visual clue, digital images are easy to manipulate due to the availability of countless editing software packages. Any image manipulation can become a forgery. Copymove forgery is a very common method of creating forge images by copying some part of the image and pastes it on the same image. In this paper, we propose a copy-move digital image forgery detection method using Fuzzy-Zernike Moments. The proposed method …
Published in Journal of Computer Technology & Applications · Vol. 7, Issue 2, 2016 · pp. 58–68 Read article
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An Approach of Likelihood Ratio Score Fusion for Appearance and Shape based Face Recognition
Abstract: AbstractThis paper deals with an approach of likelihood ratio based score fusion technique where appearance and shape based facial features have been used to enhance the efficiency of existing face recognition system. Active Shape Model (ASM) has been used to extract the appearance and shape based facial features. Two different types of features have been used in this work in such a way that when the appearance based feature contains …
Published in Journal of Computer Technology & Applications · Vol. 4, Issue 3, 2013 · pp. 1–8 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 4, 2023 Read article
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Aerodynamic Optimization of UAV Wings Using Machine Learning
Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly deployed across defense, transportation, agriculture, and environmental monitoring, demanding improved aerodynamic efficiency to enhance endurance, stability, and payload capacity. Traditional aerodynamic optimization approaches, relying on computational fluid dynamics (CFD) simulations and wind tunnel experiments, are often time-consuming and computationally expensive. This study proposes a machine learning (ML)-driven framework for the aerodynamic optimization of UAV wing geometries, aiming to significantly reduce design cycles while improving …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 1–7 Read article
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Bias Detection and Accuracy Enhancement in Voice-based Banking Authentication Using Deep Learning
Abstract: Biometric systems have become an integral part of how many people access banking services today, and voice verification systems can be a secure and easy-to-use source of banking authentication that does not require any physical contact with the bank or any other person. From the security perspective, these systems would normally provide an effective means of identifying an individual but frequently exhibit bias with respect to demographics such as the …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
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Survey on Progress in Agricultural Yield Prediction-from Machine Learning to Deep Learning
Abstract: Machine learning has offered new prospects for data-intensive study in the multidisciplinary field of Agri-technology, especially with the rise of big data systems and advanced computers. Machine learning is a powerful decision-making tool for predicting crop yields, as well as determining which crops to plant and what activities to engage in during the crop's growing season. To facilitate the study of the prediction of the agricultural yield many techniques of …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 12, Issue 1, 2022 · pp. 6–16 Read article
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Automatic annotation of reading using Speech Recognition: A pilot study
Abstract: Speech is a time-varying continuous stimulus. Analyzing a speech sample is generally done by transcribing it which can be considered to be a time-consuming process. A time annotated transcription is required for a detailed evaluation of the speech sample to study the language and prosodic features. The focus of this paper is to develop a tool to automatically segment audio recordings into silences and chunks of speech corpus and further …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 5, Issue 2, 2018 · pp. 25–29 Read article
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A Robust Automatic Algorithm for Extraction of Blood Vasculatures from Retinal Images
Abstract: AbstractIn this proposed algorithm, an efficient method for extraction and segmentation of blood vasculatures from the retinal eye images is proposed. For finding the features and abnormalities like Fovea, macula, Red lesions and exudates, blood vasculature extraction is one of the most important steps. The proposed algorithm uses tactical combination of Green, L and Y channel of Retinal image, which gives a more accurate and efficient result than the single …
Published in Recent Trends in Programming languages · Vol. 6, Issue 2, 2019 · pp. 1–7 Read article
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Advancing EEG Technology for Affordable and Effective Epilepsy Detection
Abstract: For a proper diagnosis and prompt treatment, epilepsy, a neurological condition marked by recurring seizures, needs to be continuously monitored. Manual interpretation is frequently used in traditional approaches for identifying epileptic seizures from electroencephalogram (EEG) signals, which can be laborious and error-prone. In this research, a novel method for automatically detecting epilepsy from EEG data using deep learning algorithms is presented. According to centers for disease control and prevention (CDC) …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 11–18 Read article
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Automatic Language Identification using Basic Signal Class
Abstract: Automatic language identification (ASLID) is a problem of identifying an unknown language from spoken utterance by a computer. A segmental approach to ASLID based on the assumption that the acoustic structure of languages can be estimated by segmenting speech into three basic classes of speech signals. This paper presents a procedure of ASLID with the details of methodology and the results without recognizing the words, but the lengths segments of …
Published in Trends in Electrical Engineering · Vol. 9, Issue 2, 2019 · pp. 12–19 Read article
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Learning-based Edge Detection for Video Sequences
Abstract: The advancing fields in video technology like that of 3D TV and Free Viewpoint Video essentially requires more information to transmit in addition with the 2D color maps. This information is the depth maps of the accompanying scenes from the videos sequences in order to facilitate rendering of arbitrary viewpoints within it. Soft computing approaches such as consisting of fuzzy logic, neural or evolutionary computation are the emerging fields with …
Published in Recent Trends in Parallel Computing · Vol. 2, Issue 3, 2015 · pp. 1–19 Read article
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Depth Map Compression by Contour Networks for Video Sequences
Abstract: The advancing fields in video technology like that of 3D TV and Free Viewpoint Video essentially requires more information to transmit in addition with the 2D color maps. This information is the depth maps of the accompanying scenes from the videos sequences in order to facilitate rendering of arbitrary viewpoints within it. In this study, we present a novel algorithm to determine the contours from the given video sequences and …
Published in Recent Trends in Parallel Computing · Vol. 2, Issue 2, 2015 · pp. 9–13 Read article
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Facial Recognition System Utilizing Real-time Deep Learning Techniques
Abstract: This research introduces an openly accessible deep learning-based framework designed for facial recognition. The system encompasses five key stages: face segmentation, detection of facial features, face alignment, embedding, and classification. Deep learning methods are employed for the extraction of fiducial points and embedding within the system. For the classification task, a Support Vector Machine (SVM) is utilized due to its efficiency in both training and inference phases. Notably, the system …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 14–20 Read article
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Exploiting Phase of Speech Signal for Speaker Recognition
Abstract: Abstract—Performance of speaker recognition system with feature based on temporal phase is presented in this paper. In the state of the art spectral feature, Mel Frequency Cepstal Coefficient (MFCC) only magnitude of the Fourier Transform of speech signal is considered while phase is ignored. The cepstral coefficients extracted from temporal phase (MFTPC) of speech signal are used as features for speaker recognition system. The performance of MFTPC feature is evaluated …
Published in Journal of Communication Engineering & Systems · Vol. 9, Issue 2, 2019 · pp. 81–87 Read article
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Online Handwritten Kannada Character Recognition and Translation to English
Abstract: Abstract—The objective of the paper is to develop a technique that can efficiently recognize hand-written characters of Kannada language and then translate the same to English language. Online recognition refers to the processing of the characters as and when it is written on digitizer and recognizes the class which it belongs to. The iball 5540U Pen Tablet is used to collect the handwritten character samples and to build the database. …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 6, Issue 2, 2019 · pp. 37–53 Read article
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Comparative Evaluation of Hibiscus Cannabinus and Solanum Trilobatum Extracts as Inhibitors for C- Steel Corrosion protection in Acidic Medium
Abstract: This study analyzed the efficacy of various inhibitors in safeguarding carbon steel against corrosion in hydrochloric acid. The compounds that were subjected to testing included Acalypha indica root extract (AIRE), Hibiscus cannabinus (HC), and Solanum trilobatum (ST) leaf extracts. The investigation focused on the inhibitory efficacy through the application of gravimetric and electrochemical impedance methods. GC-MS and FTIR were employed to investigate the features of the inhibitors and co-inhibitors. Tafel …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 555–565 Read article
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Identifying sustainability traditional solutions of Dhamar house
Abstract: The world is facing numerous issues from environment pollution, from natural disasters resulting, from climate change, and from the waste of natural resources, has focused specific attention to sustainable development. The house design has different characteristics according to the culture and environmental conditions. The study attempts to answer that, is the traditional architecture of Yemen consists with the principles of sustainable architecture? Moreover, what are sustainable solutions used in the …
Published in International Journal of Rural and Regional Development · Vol. 1, Issue 2, 2023 · pp. 01–14 Read article
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Artificial Neural Network-Based Multifocus Image Fusion
Abstract: Fusion of multiple images is needed for combining information contained in images obtained using different imaging devices or different camera settings. Due to the physics of optical lenses present in these devices, it is difficult to capture an image that has all the relevant objects well in focus. Thus, artificial neural network (ANN)-based multifocus image fusion method in YCbCr color space is proposed. Input images are first mapped from RGB …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 3, 2018 · pp. 16–23 Read article