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147 articles for “Neural networks”
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Fuzzy Logic, Artificial Neural Network and Genetic Algorithm over Sylvester Law of Inertia based Data Analysis Technique
Abstract: ABSTRACT Compactness of the Fuzzy Logic (FL), Artificial Neural Network (ANN) and Genetic Algorithm (GA) is applied to analyze the data. This paper presents a foundation for the same in compact form over the Sylvester’s Law of Inertia (SLI). The sequence of FL, ANN and GA is studied for deciding the source of output data. The data interacts with the academic institutes. The academic planning is based on the existed …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 5, Issue 1, 2019 · pp. 22–29 Read article
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Statistical and Artificial Neural Network for the Determination of Thermo-Physical Properties of Fomoditine Drug Using Mixed Hydrotropy
Abstract: The experimental determination of thermo-physical properties of fomoditine drug–mixed hydrotrope concentration mixture is very time consuming as well as tedious process. Any tool helpful in estimation of these properties without experimentation can be of immense utility. In present work, other tools of determination of properties of fomoditine drug–mixed hydrotrope concentration blends were tried. A traditional statistical technique of linear regression (principle of least squares) was used to estimate the specific …
Published in International Journal of Chemical Engineering and Processing · Vol. 1, Issue 2, 2015 · pp. 1–6 Read article
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Enhancing Glaucoma Detection with Convolutional Neural Networks: A Data-Driven Approach
Abstract: One of the main causes of irreversible blindness is glaucoma, which is characterized by certain alterations in the optic nerve that over time can impair vision. Manual evaluations, while invaluable, are challenged by inconsistencies, subjectivity, and the extensive time required. The study employed a dataset comprising retinal images annotated by experts. By using Convolutional Neural Networks (CNNs) to study and recognize important patterns in eye images, it was possible to …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 11, Issue 1, 2025 · pp. 1–6 Read article
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Neural Networks and Fault Diagnosis in Integrated Analog Circuits
Abstract: Abstract—This is a research paper on changing the learning speed of analogue integrated circuits by solving the complications in network scales and diagnosis of circuit faults in neural network and integration with arithmetic mechanisms at a distributed network.
Published in International Journal of Analog Integrated Circuits · Vol. 1, Issue 1, 2015 · pp. 13–17 Read article
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Convolution Neural Network Model to Classify Photo Gallery on an Android Device
Abstract: The classification of images is a classic topic in the domains of image processing, computer vision, and machine learning. Convolution Neural Networks, a sort of deep learning that falls under the Machine Learning sub-domain, have been used in this model. This model was inspired by the problem that students experience at the end of the academic year is that their phones become cluttered with photos from various sources. The aim …
Published in International Journal of Analog Integrated Circuits · Vol. 8, Issue 1, 2022 · pp. 9–17 Read article
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Study of ECG Signal by Using Different Order Kaiser Window and Neural Network
Abstract: The morphology of ECG signal has been used for recognizing much variabilitys’s of heart activity, so it is very important to get the parameters of ECG signal. In this paper used to design different order of FIR filter and Kaiser window techniques and result train by neural network. Keywords: ECG data signal, FDA tool, nn tool
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 2, Issue 1, 2016 · pp. 15–19 Read article
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Artificial neural network based classification of varieties of thin and thick fabric images
Abstract: Abstract: The proposed work focuses on classification of varieties of thin and thick fabric materials from images. The morphological operations such as erosion and dilation are performed. Morphological features namely, avg_moments, average_area, roundness, max_area, average_perimeter, average_eccentricity, circularity and average_equivalent_diameter are extracted. The prediction is carried out using artificial neural network. The classification rates of 84.84% and 90.90% are obtained for thin and thick fabric images. The classification rates for varieties …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 4, Issue 1, 2018 · pp. 31–41 Read article
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Diabetic Retinopathy Detection from Retinal Images Using Convolutional Neural Network
Abstract: Diabetic retinopathy (DR) is a popular problem of diabetes and the major reasons of loss of sight in the active inhabitants. Many of the problems of DR can be avoided by blood glucose manage and regular remedy. Since the kinds and the difficulties of DR, it is actually hard for DR detection in the time-consuming regular analysis. This document is to effort towards discovering an automated method to sort out …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 9, Issue 1, 2023 · pp. 8–17 Read article
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Image Denoising by Sigma Estimation based Convolution Neural Network
Abstract: Abstract Image denoising process gains more attention due to its effective denoising performance. This paper proposed the convolution feedforward network with sigma estimation and without sigma estimation to provide the prior information to the CNN and without sigma, it does not come to CNN. The outcomes with CNN and without CNN use image denoising and reduce the MSE and enhance the PSNR. Keywords: Image Denoising, Deep Learning, Convolution Neural Network …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 4, Issue 2, 2018 · pp. 18–26 Read article
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Neural network based prediction of shear wave velocity for soils
Abstract: The paper presents a study on the prediction of the shear wave velocity (Vs) for all soils using ANN model from cone penetration test data. The input parameters in the obtained of ANN models were vertical effective stress, sleeve friction, cone tip resistance and output was the shear wave velocity. These parameters were considered to construct the ANN model which has 3-2-1 topology in prediction of shear wave velocity. Further, …
Published in International Journal of Geological and Geotechnical Engineering · Vol. 5, Issue 2, 2019 · pp. 23–34 Read article
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Predictive Modeling of Dengue Mosquito Populations Using Artificial Neural Networksfor Effective Zapping Solutions
Abstract: The World Mosquito Programme highlights the significant global threat posed by dengue fever, estimating that over half of the world's population is at risk, with approximately 390 million cases reported annually. In 2023, India witnessed a substantial increase in dengue cases, recording over 270,000 cases compared to 74,000 in 2017. Dengue Virus (DENV) transmission occurs through Aedes Aegypti Mosquito bites, and with no specific treatment or vaccine available, effective management …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 10, Issue 1, 2024 · pp. 27–36 Read article
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Detecting COVID_19 in X-ray images using artificial neural network
Abstract: In this paper, we propose a method for detecting COVID-19, which is most important for now days in lowering mortality rates. COVID-19 had a rapid impact on our daily lives, businesses, and global trade and transportation. Chest CT scans and CT x-rays reveal particular radiographic abnormalities in people with COVID-19 by means of faster and more efficient representation of the patient's lung that enables for the detection of viral phenomena. …
Published in International Journal of Broadband Cellular Communication · Vol. 8, Issue 1, 2022 · pp. 32–38 Read article
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Robot Kinematics and Neural Networks: A Summary
Abstract: The robot control problem can be divided into two main areas: kinematics control (coordinating the kinematics chain links to generate the robot’s desired motion) and dynamics control (driving the mechanism's actuator to obey the programmed positions and speeds). Further, the kinematics analysis is performed in two ways in robotics, with forward kinematics (FK) and inverse kinematics (IK). FK is defined as the mapping from joint space to Cartesian space (also …
Published in International Journal of Analog Integrated Circuits · Vol. 5, Issue 2, 2019 · pp. 40–45 Read article
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Development of Empirical Relationships Between Input and Output Parameters of Sponge Iron Process Using Neural Network
Abstract: In the present study, estimation of optimum input parameters corresponding to desired output parameters is carried out for a typical sponge iron process. For this purpose data of rotary kiln of the process are collected. It includes temperatures profiles inside the rotary kiln and flow rates of air, iron ore, feed coal, slinger coal and sponge iron. These data are analysed using ANN and group method of data handling (GMDH) …
Published in International Journal of Renewable Energy and its Commercialization · Vol. 1, Issue 2, 2015 · pp. 6–19 Read article
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Artificial Neural Networks based Four-Leg Matrix Converter for Linear and Non-Linear Load
Abstract: The 4-leg matrix converter, which it is capable of providing a 3-phase plus neutral supply from a standard balanced 3-phase source . Tralatitious 3x3 matrix converters deliver bounded use in this application as they are only capable of supplying a poised three-phase payload. It would be suitable to be able to power unbalanced and nonlinear loads ,requiring that the converter provides a neutral connection .This goal can be achieved by …
Published in International Journal of Power Electronics Controllers and Converters · Vol. 2, Issue 1, 2016 · pp. 45–53 Read article
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Facial Emotion-Based Stress Detection Using CNN and Haar Cascade Algorithms
Abstract: Understanding human conduct requires the ability to recognize facial emotions, which has applications in everything from human–computer interaction to psychological wellness monitoring. This research provides a new approach to stress detection using convolutional neural networks and Haar Cascade classifiers. The suggested method uses convolutional neural network to recognize facial expressions and Haar Cascade algorithm for face detection. The methodology begins with preliminary processing of the input photos, followed by face …
Published in International Journal of Microwave Engineering and Technology · Vol. 10, Issue 2, 2024 · pp. 1–11 Read article
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The Implementation of Machine Learning in the Search to Fight Plant Disease
Abstract: The agriculture business loses money and time due to plant diseases. Diagnosing disease accurately takes skill and devotion. Infected plants may have spots or streaks of a different color on their leaves. Several fungal, bacterial, and viral species can also infect plants. Individual plant disease signs and indications are assessed. Neural network applications are growing. Recent research studies have determined how well machine learning reviews traditional plant disease diagnosis methods. …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 1, 2024 · pp. 25–34 Read article
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Hybrid Machine Learning Model for EfficientBotnet Attack Detection in IoT Environment
Abstract: The rapid advancement and widespread adoption of internet technologies have led to a surge in cyber-attacks, with botnet attacks emerging as particularly detrimental. Identifying botnet activities is increasingly challenging due to the diverse attack vectors and the evolving nature of malware. As the Internet of Things (IoT) continues to expand, network devices become more vulnerable to these sophisticated attacks, resulting in significant security breaches and financial losses. In order to …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 2, 2026 · pp. 31–38 Read article
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Enhancing Image Quality with Deep Learning Techniques for Restoration and Denoising
Abstract: Abstract: Clear and high-quality images have become more and more necessary in recent years due to the rapid development of computer vision-based autonomous systems, including autonomous driving, underwater robots, video surveillance, and medical imaging. However, real-world circumstances, such as inclement weather, underwater scenes, and moving cameras, can lead to poorer-quality photographs. These degradations, which include color distortions, noise, and blurring, hurt how well visual systems accomplish tasks like target tracking, …
Published in International Journal of Broadband Cellular Communication · Vol. 10, Issue 2, 2024 · pp. 1–6 Read article
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Advanced Diabetic Retinopathy Detection Using Deep Learning Classifiers
Abstract: Diabetic Retinopathy (DR) is an eye condition that arises from diabetes-related complications, making early detection essential for effective treatment. As diabetes advances, an individual’s vision may deteriorate, potentially resulting in diabetic retinopathy. This condition is divided into two primary types: Non-Proliferative Diabetic Retinopathy (NPDR) and Proliferative Diabetic Retinopathy (PDR). Early treatment to maintain a strategic distance from a change less visual impedance is basic as it may save diabetic retinopathy …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 1, 2025 · pp. 26–33 Read article