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415 articles for “neural network method”
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Unsupervised Learning Techniques in Neural Network for Face Recognition
Abstract: This paper represents the review of systematic comparison between of unsupervised learning algorithms for face recognition. In neural network, different algorithms are used for face recognition. Each algorithm has different accuracy factors. Commonly these methods asset a set of base images and serve faces as linear combo of images. In our proposed review, firstly we discuss about the face detection using neural network along with the concept of digital image …
Published in Journal of Advancements in Robotics · Vol. 7, Issue 1, 2020 · pp. 25–29 Read article
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Optimized Sentiment Analysis Through TextBlob and Hybrid RNN Models
Abstract: In today’s world, analyzing people’s feelings from what they write online has become very important. This is because there is a large amount of content created by users. To make this analysis accurate and fast, we present a method. This method uses a mix of two approaches: one that looks up words in a dictionary and another that uses computer learning. TextBlob is an affordable tool for getting an initial …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 29–28 Read article
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Computational Intelligence and Neuro-Fuzzy Modelling of Polymer Composites: A Critical Review of Performance Prediction and Optimization
Abstract: The increased variety in polymer matrices, reinforcements, fillers, and processing parameters has led to the need to better understand the structure-property, process-property relationships in order to accurately predict and optimize the performance of polymer composites. This paper reviews the applications of computational intelligence methods in polymer composites, with special focus on artificial neural networks, adaptive neuro-fuzzy inference systems, machine learning techniques, and hybrid optimization. The literature is analyzed based on …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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CNN-BILSTM Architectures for Handwritten Signature Verification: Insights and Innovations
Abstract: Verifying handwritten signatures is essential for identity authentication to guard against fraud and guarantee security across a range of platforms. The approaches and developments in handwritten signature verification are examined in this review, with an emphasis on both offline and online techniques. While online methods use dynamic information like stroke order and speed, collected by specialized devices, offline verification uses scanned photographs of signatures. Even if technology is moving toward …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 43–50 Read article
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Evaluation of Ensemble and Deep Learning Classifiers on CSE-CIC-IDS2018 Dataset for Intelligent NIDS
Abstract: Network Intrusion Detection System (NIDS) plays an active role in preventing cyberattacks by early detection of threats before it really starts affecting targeted information services. Over the years, many intrusion detection system (IDS) have been developed applying signature or rule-based approach to prevent unauthorised access of network or computer devices. However, ever growing landscape of cyberattacks in recent years has motivated present day researchers to design and develop more accurate …
Published in Current Trends in Information Technology · Vol. 13, Issue 1, 2023 · pp. 1–11 Read article
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Ventricular Arrhythmia Detection Techniques for ECG Signal: A Survey Approach
Abstract: Electrocardiogram (ECG) represents the electrical activity of the heart and is used to measure the rate and regularity of heartbeats. In this paper we propose a method for an Independent Component Analysis (ICA) based detection and classification of the ventricular arrhythmia. The malignant ventricular arrhythmia database from www.physionet.org/physiobank/database/vfdb has been utilized for evaluating the algorithm over MATLAB interface. This scheme assimilates ICA and probabilistic neural network for classifying critical arrhythmia …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 5, Issue 1, 2015 · pp. 25–30 Read article
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Optimizing Machinability in Wire EDM of AISI P20 Steel Employing Composite Material Wires with Hybrid Neural Network Approach
Abstract: AISI P20+Ni steel is extensively used for forging dies, plastic moulds, and automotive die components due to its excellent polishability, hardness, and homogeneity. This research utilizes Wire Electrical Discharge Machining (WEDM) to process pre-hardened AISI P20+Ni steel, focusing on minimizing both recast layer thickness (RLT) and kerf width (KW). The performance of wires made from composite materials, including zinc-coated brass wire (ZBW), cryogenically treated ZBW (CZBW), and ultrasonic vibration-assisted brass …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1120–1133 Read article
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CNN based Gesture Recognition for ISL
Abstract: AbstractGesture recognition has always been at a peak when it comes to computer vision and human-computer interaction (HCI). Hand gestures can be used for interaction with systems like managing UAVs, medical devices, videogames, etc. In this paper, the main focus is on handicapped people, who are physically unable to speak or listen. With the help of computer interaction, gestures will be recognized. As, the same gesture by another people differs, …
Published in Journal Of Network security · Vol. 8, Issue 3, 2020 · pp. 11–19 Read article
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Bearing Defect Diagnosis: An Approach for Manufacturing Industries Using Wavelet Transform Based Features
Abstract: To maintain reliability in the manufacturing units, industries have concentrated their attention on the condition based maintenance. Fault detection and diagnosis are the two of three condition based maintenance mainstays. Bearing is one of the most important and essential components of the rotating machines. Hence, the researchers have shown their interest in bearing fault detection and diagnosis from the last few years. They mainly use bearing vibration as fault characteristics …
Published in Journal of Microelectronics and Solid State Devices · Vol. 4, Issue 1, 2017 · pp. 15–21 Read article
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Malaria Parasite Detection in Thin Blood Smear Images Using Deep Learning
Abstract: Algorithms in deep neural networks are being used to show the presence of malaria and to estimate the depth of infection by automatically counting individual uninfected and infected RBCs in images of thin blood smears. During the training period, the relationship was tried on a set of 13600 images from several thin blood spreads and experiment was conducted. My dataset is divided into 80% for training and 20% for testing. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 1, 2020 · pp. 28–32 Read article
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Advancements in Agricultural Forecasting: A Review of Machine Learning Based Crop Yield Prediction
Abstract: Agricultural productivity plays a critical role in global food security, and accurate crop yield prediction is essential for optimizing resource allocation and decision-making in farming. The rapid advancements in Machine Learning (ML) and Deep Learning(DL)have transformed agricultural forecasting, enabling data-driven approaches for crop prediction. This review paper provides a comprehensive analysis of various ML and DL techniques applied in crop yield forecast, highlighting the ineffectiveness, challenges, and future directions. The …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 32–38 Read article
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Modeling and Simulation of a Hybrid Solar-Wind System with Adaptive Neural Network MPPT Control in MATLAB/SIMULINK
Abstract: Over the last ten years, there has been an increasing demand for the electrical powersupply. The installation of power generators (PGs) is expensive and time-consuming. Solar powerplants are therefore thought to be a practical substitute for supplying the present demand forelectricity. The primary challenges with solar plants, however, are output power balancing andcritical maintenance. A proper technique is needed to lessen output power balance andmaintenance issues in solar facilities. For …
Published in Journal of Power Electronics and Power Systems · Vol. 13, Issue 2, 2023 · pp. 53–61 Read article
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Fingerprint Recognition for Crime Scenes Using Deep Learning
Abstract: Crime-scene fingerprint photos are crucial hints for resolving ongoing cases. Using deep machine learning and convolutional neural networks, we provide a comprehensive crime scene fingerprint identification method in this research (CNN). Precision photography and sophisticated physical and chemical processing techniques are used to collect images from crime scenes, which are then kept as databases. It can be challenging to categorize the photographs taken from the crime scene because they are …
Published in Trends in Opto-electro & Optical Communication · Vol. 12, Issue 2, 2022 · pp. 13–18 Read article
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Predicting Employees Performance using Data Mining Techniques
Abstract: Human resources management (HRM) has become one of the essential interests of managers and 4decision-makers in almost all types of businesses to adopt plans for correctly discovering highly qualified employees. In this research, data mining techniques were utilized to build a classification model for predicting the performance of employees using a real dataset. For this, we are using different methods such as support vector machine, Logistic Regression and Neural Network. …
Published in Recent Trends in Parallel Computing · Vol. 8, Issue 1, 2021 · pp. 4–13 Read article
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Quantum Leaps: How Quantum Computing Shapes the Evolution of Artificial Intelligence
Abstract: Quantum computing leverages quantum mechanical phenomena to enable powerful new forms of computation. With the ability to dramatically exceed the capabilities of classical supercomputers on select complex problems, many researchers anticipate revolutionary impacts of quantum computing on a variety of fields, including artificial intelligence. This research proposal outlines an investigation analyzing the intersection of quantum computation and artificial intelligence. The key research questions explore how quantum algorithms and hardware may …
Published in Recent Trends in Parallel Computing · Vol. 10, Issue 3, 2023 · pp. 7–17 Read article
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Impact of ML in Evolution of Recommender Systems: A Review
Abstract: Recommender systems have become indispensable tools in today's digital era, catering to the overwhelming demand for personalized recommendations in various domains such as e-commerce, content streaming, and social media. The continuous growth of data and user interactions has necessitated the integration of advanced machine learning (ML) techniques to enhance the accuracy and efficiency of these systems. This study provides a thorough analysis of current developments in machine learning methods used …
Published in E-Commerce for Future & Trends · Vol. 10, Issue 2, 2023 · pp. 26–32 Read article
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A Comprehensive Survey of Polymer Detection Techniques and Computer-Based Analysis Methods for Advanced Material Characterization
Abstract: Polymers are widely used in aerospace, automotive, biomedical, packaging, electronics, and manufacturing industries because of their lightweight nature, durability, and versatility. Accurate polymer identification and characterization are essential for quality control, recycling, performance assessment, and the development of advanced materials. Characterization helps determine important properties such as chemical composition, molecular structure, thermal stability, mechanical strength, and surface morphology, which influence material performance and application suitability. Traditional polymer detection methods include …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 921–929 Read article
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Compact Method for Analyzing Big Data
Abstract: Big Data Analysis (BDA) method is proposed in this paper. A compact method (K-Means Cluster, Generalised K-Means Cluster, C-Means, Fuzzy Means, Fuzzy Numbers, Fuzzy Set, Fuzzy Logic, Neural Network, Genetic Algorithm) based big data analysis is presented in this paper. There are four models are presented as, probabilistic model, possibility model, fuzzy model and variance model. A compact algorithm is illustrated also in this paper.Keywords: Big Data, K-Means Cluster, Generalised …
Published in Journal of Advanced Database Management & Systems · Vol. 7, Issue 2, 2020 · pp. 5–14 Read article
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Pneumonia Detection Using Deep Learning–Convolutional Neural Network
Abstract: Pneumonia disease is associate in nursing infectious and deadly illness in metabolic process that is caused by microorganism, fungi, or a deadly disease that infects the human respiratory organ air sacs with the load choked with fluid or pus. Chest X-rays area unit the common methodology accustomed diagnose respiratory disorder and it wants a health worker to gauge the results of X-ray. The hard methodology of detection of the respiratory …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 1, 2021 · pp. 9–16 Read article
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Innovative CNN Strategies for Superior Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a fundamental problem in the field of computer vision and machine learning with numerous applications, such as postal code recognition, bank check processing, and digitizing historical documents. Convolutional Neural Networks have demonstrated remarkable success in various image recognition tasks, making them a popular choice for digit recognition. In this study, we present an enhanced approach to handwritten digit recognition using CNNs. Handwritten digit recognition plays a …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 1, 2024 · pp. 27–34 Read article