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398 articles for “Neural Network Techniques”
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Review on Digital Filter Design Using Artificial Neural Network
Abstract: AbstractThis paper provides a survey report on designing digital FIR filters with the help of artificial neural network (ANN) proposed by many researchers who gives a better results and easy way to design a filter. It includes types of filters, window techniques, artificial neural network, comparative analysis of various existing work. This paper gives a better way to analyze various techniques used to design FIR filters. This survey report provides …
Published in Journal of Communication Engineering & Systems · Vol. 6, Issue 2, 2016 · pp. 9–15 Read article
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Comparative Analysis of Data Augmentation Techniques in CNN-based Classification of Atelectasis
Abstract: This research delves into the critical issue of atelectasis, its causes, and potential complications if left untreated. Leveraging deep learning algorithms, particularly convolutional neural networks (CNN), the paper explores their application in medical image analysis, focusing on the detection of atelectasis using the “chestX-ray8” database. The study compares various data augmentation techniques for improved accuracy, showcasing the importance of augmentation in enhancing model generalization. Through meticulous experimentation and evaluation, the …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 3, 2024 · pp. 1–8 Read article
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Optical Character Recognition in the computering
Abstract: In today's world, advances in advanced scientific techniques drive more human communication limits in different areas of technology. One of these areas is the field of character recognition known as OKR. A simple way to store and remove in formation in these paper documents is in the computer system and then stores them as images. In this fast paced world there is a great need to digitize printed documents and …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 5, Issue 1, 2018 · pp. 1–5 Read article
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Optimization Study by Response Surface Methodology and Artificial Neural Network on the Culture Parameters of Citric Acid Bioproduction from Sweet Potato Peels
Abstract: In the cause of this research work, two steps enzymatic hydrolysis of sweet potato peel was carried out respectively. The effect of α-amylase dose, reaction time, and reaction temperature and biomass weight on glucose concentration was investigated carefully. The response surface methodology (REM) predicted the highest reducing sugar concentration at liquefaction to be 74 g/L, at the following optimized conditions; temperature of 45°C, α-amylase dose 0.7 %v/v, biomass weight 22.345 …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 9, Issue 1, 2022 · pp. 30–38 Read article
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Application of AI Techniques in Three-phase Shunt Active Power Filter in Unbalanced and Distorted Supply Conditions
Abstract: This paper deals with a new improved model of the shunt active power filter having the control scheme using Artificial Neural Networks (ANN) technique in unbalanced and distorted supply system. In this paper, three soft computing techniques viz; Genetic algorithm, Fuzz logic, neural network are used. The simulation results using MATLAB model confirm that combination of these algorithms together create an optimum system, which clearly proves the effectiveness of the …
Published in Journal of Power Electronics and Power Systems · Vol. 3, Issue 3, 2013 · pp. 15–26 Read article
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Mechanical Strength Prediction of Nano-Silica Concrete Composites Using Machine Learning Techniques
Abstract: Nano-silica, or nanosilica, refers to silicon dioxide nanoparticles, which are a kind of silica (SiO₂) with diameters that often fall below 100 nanometers. This nanomaterial has attracted considerable attention because of its distinctive characteristics and diverse array of uses, notably in augmenting the performance of materials such as concrete. The integration of nanoparticles with cementitious matrix in nano-silica concrete offers a viable approach to improving the mechanical characteristics and longevity …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 963–973 Read article
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An Accuracy Improvement in Facial Verification through Siamese Neural Networks
Abstract: Due to the ever-growing number of digital photos on the Internet, the task of automatically analysing images to extract semantic content has become quite important in recent years. In order to successfully organize the photographs, image indexing and image retrieval strategies need top-notch, effective image analysis and pattern recognition algorithms that can extract relevant semantic data. Face recognition plays a critical role in a variety of real-world applications, including AI-driven …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 10, Issue 2, 2023 · pp. 1–9 Read article
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Assessing the Performance of DL Methods in Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a computer vision task that involves the automatic identification and classification of hand-written digits. The objective is to develop models capable of accurately recognizing and distinguishing digits handwritten by humans. With the development of machine learning and deep learning techniques, this field has advanced remarkably. The convolutional neural network (CNN) is the most often used technique for this purpose. By utilizing CNN, the model can learn …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 25–32 Read article
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Data Maneuvering Identification
Abstract: Copy-move forgery detection (CMFD) is unquestionably one of the most active research areas in the field of blind image forensics. Most existing algorithms rely on block and key-point strategies, either separately or jointly. Recent applications of deep convolutional neural network (CNN) techniques include image forensics, image hashing retrieval, and picture classification. These techniques have outperformed more conventional techniques in many areas. In this study, a brand-new convolutional neural network based …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 99–104 Read article
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Enhancement in Biomedical Polymer Nanocomposites: Biocompatibility and Mechanical Property Predictions using Machine Learning
Abstract: A machine learning (ML)-based framework is developed and validated through experimental analysis and comparative modeling to enhance system dependability and improve prediction performance. The proposed framework includes key stages such as data preprocessing, feature evaluation, model training, and performance benchmarking to determine the most effective prediction technique. Several machine learning models were evaluated, including Ensemble models, Artificial Neural Networks (ANN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 275–296 Read article
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Measurement of Program Outcomes Attainment for Engineering Graduates by using Neural Networks
Abstract: AbstractThis paper aims to provide an evaluation method for the attainment of program objectives for engineering graduates as defined by NBA (National Board of Accreditation). As NBA requires specific evaluation techniques and measurement methods for measuring the attainment of course outcomes, program outcomes and program educational outcomes; this paper provides a solution of the measurement techniques using neural networks. The performance of all the students of a batch can be …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 2, 2015 · pp. 21–24 Read article
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Speaker Identification using Hopfield Neural Network based Classifier
Abstract: The aim of this work is to enhance the performance of speaker identification using Hopfield neural network algorithm. Speech signals are collected from VALID Audio-Visual dataset and some speech signal pre-processing techniques are applied to process the speech to feed the Hopfield neural network algorithm. Filtering technique is applied to remove the noises from the speech signals. MFCC based standard speech feature extraction technique is used to extract the speech …
Published in Journal Of Network security · Vol. 3, Issue 2, 2015 · pp. 32–35 Read article
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Artificial Neural Network Model for Stock Market Forecasting
Abstract: AbstractIn recent years, many attempts have been made to predict the behavior of bonds, currencies, stocks or stock markets. Neural networks, as an intelligent data mining method, have been used in many different challenging pattern recognition problems such as stock market prediction. The aim of this paper is to predict stock market using artificial neural networks (ANNs). The authors used feed forward neural network trained by back-propagation algorithm to make …
Published in Journal of Computer Technology & Applications · Vol. 5, Issue 1, 2014 · pp. 7–12 Read article
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An Approach of Multi-modal Biometric Iris and Speech based Person Recognition System with Decision Fusion Technique
Abstract: This paper presents a unique approach of multi-modal iris and speech feature based person recognition system. Iris images and speech signals are taken from CASIA iris database and NOIZEUS speech database respectively. Iris features are extracted after applying iris images noise removing and image pre-processing techniques. On the other hand, speech signal noise removing, start-end points detection algorithm, silence parts removal, windowing and feature extraction techniques are applied to extract …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 2, Issue 2, 2015 · pp. 5–10 Read article
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Application of Neural Network Analysis to Correlate the Properties of Plasma Spray Coating
Abstract: Thermal spray coatings are more often being demanding process at the recent stages of industrial design processes to become fundamental element of the engineering system. The aim of the present paper is to develop a model-based estimation and control for regulating the coating adhesion strength, by using neural network. This proposed model permits cost reduction by the possibility of adjusting the parameter of the process for each of the desired …
Published in Journal of Materials & Metallurgical Engineering · Vol. 2, Issue 1-3, 2012 · pp. 1–10 Read article
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Classification and Detection of Brain Tumor using Convolutional Neural Network
Abstract: Tumors are masses created when brain cells multiply uncontrollably. A brain tumor is the medical term for this condition. Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Developing a treatment plan is essential to raising a patient's standard of living. Tumors in different regions of the body are evaluated using a variety of imaging techniques, with MRI pictures being utilized mostly for …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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Estimation Techniques in Image Restoration - A Survey Approach
Abstract: In the present paper a comparative study of various estimation techniques based on neural network, MATLAB, partial differential equation (PDE) and other proposed models for image restoration are been discussed. An image may be distorted, noisy or blurred and not suitable for extracting desired information or data, so it needs to be restored for desired application. Image restoration techniques are oriented towards modeling the degradation, blur and noise and applying …
Published in Current Trends in Signal Processing · Vol. 4, Issue 1, 2014 · pp. 11–16 Read article
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Predictive Modeling System for Automated Skin Lesion Classification Using Deep Neural Networks and Voting Ensembles
Abstract: Skin cancer is one of the most prevalent cancers globally. Early and accurate diagnosis is critical for timely treatment and improved prognosis. This study presents a predictive modeling system for automated classification of skin lesions from dermoscopic images using deep neural networks and voting ensemble techniques. A customized 16-layer convolutional neural network architecture is developed for feature learning from lesion images. The concept of horizontal voting ensemble is implemented by …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 29–35 Read article
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Fertilizer Prediction Using Machine Learning
Abstract: Fertilizer prediction is a critical aspect of modern agriculture, aimed at optimizing resource utilization while maximizing crop yields. In recent years, machine learning (ML) techniques have emerged as powerful tools for addressing this challenge by leveraging data-driven approaches to predict the optimal type and quantity of fertilizer required for different crops and soil conditions. This research paper provides a comprehensive review of the existing literature and methodologies employed in fertilizer …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 2, 2024 · pp. 26–35 Read article
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Artificial Intelligence in Entomology: Global Advances, Applications, and Future Directions in Insect Research and Pest Management
Abstract: Artificial Intelligence (AI) is transforming entomology by enabling scalable, data-driven approaches to insect identification, ecological monitoring, and sustainable pest management. This review synthesizes recent global advances in AI applications across taxonomy, behavioral ecology, predictive modeling, and precision agriculture. Machine learning and deep learning techniques—including convolutional neural networks, acoustic classification models, and ensemble predictive algorithms—have demonstrated high classification accuracies (often exceeding 90% under controlled conditions) and improved early detection of pest …
Published in International Journal of Insects · Vol. 3, Issue 1, 2026 · pp. 29–40 Read article