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628 articles for “neural”
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Radial Basis Function Neural Networks for Rainfall-Runoff Modeling
Abstract: Rainfall-runoff process is purely nonlinear and varies spatially as well as temporally. Any hydrological model requires many parameters which represent different components of the process. Availability of all the parameters is difficult for any catchment and probabilistic generation of such type of data is impossible. Under such circumstances, artificial neural networks (ANNs) have proven to be a better tool to model the rainfall-runoff process with minimum available data. The present …
Published in Journal of Water Resource Engineering and Management · Vol. 1, Issue 2, 2014 · pp. 11–18 Read article
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Estimation of Discharge Over the Compound Sharp-Crested Weir using Artificial Neural Networks and Genetic Programming
Abstract: Truncated sharp crested weirs are used to measure flow rate and to control water surface upstream, in irrigation canals and laboratory flumes. The main advantages of such weirs are, ease of construction and capability of measuring a wide range of flows with sufficient accuracy. Artificial neural networks (ANNs) and genetic programming (GP) have recently been used for the estimation of hydraulic data. In this study, they were used as alternative …
Published in Journal of Water Resource Engineering and Management · Vol. 2, Issue 3, 2015 · pp. 28–37 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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Temporal Information Extraction from Textual Data using Long Short Term Memory Recurrent Neural Network
Abstract: Temporal information extraction from raw text is always challenging. It is time consuming and sometimes difficult to extract temporal expression manually. For this reason, an automatic system is a demand to find the temporal expressions from the textual data automatically. In this paper, we have developed a temporal information extraction system using Long Short Term Memory (LSTM) recurrent neural network (RNN) along with word embedding where temporal expressions are extracted …
Published in Journal of Computer Technology & Applications · Vol. 9, Issue 2, 2018 · pp. 1–6 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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Numerical Simulation of Deep Convolutional Neural Network Based Flower Classification System
Abstract: There are more than 250,000 recognized floral plant forms in 350 families. Further more the order, the plant checks of structures, the gardening industry, live plantations and scientific flower classification instructions depend on fruitful flower classification, including a content-based image recuperation. A wide range of applications also includes flower portrayals. The manual classification is however tedious and tiresome, particularly when the picture foundation is perplexing, with a huge number of …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 3, 2021 · pp. 23–31 Read article
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Development of Intensity-based Segmentation Technique for Meningioma Tumor Detection in MRI Images
Abstract: There are many types of brain tumors. Some brain tumors detection system using segmentation and classification of MRI images. Brain tumors can have any shape or cut. This encourages us to use high-capacity deep neural networks. Segmentation task and 8000 images for classification task of our neural network and found the best architecture to use. convolutional neural network. In recent years, the three most common forms of brain tumours—glioma, meningioma, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 11, Issue 03, 2022 · pp. 50–54 Read article
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Neural Sheath Liposarcoma: A Case Report
Abstract: Liposarcoma is a malignant mesenchymal tumor of the adipose tissue [1]. Liposarcomas most frequently arise from the deep-seated stroma rather than the submucosal or subcutaneous fat [2]. The most recent World Health Organization classification of soft tissue tumors recognizes five categories of liposarcomas: (1) well differentiated, which includes the adipocytic, sclerosing, and inflammatory subtypes; (2) de differentiated; (3) myxoid; (4) round cell; and (5) pleomorphic [2–4]. The anatomical distribution of …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 2, Issue 3, 2012 · pp. 8–10 Read article
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Polypyrrole-Based Conductive Polymer-Gated Single Electron Transistor with Deep Neural Network Assistance for Biomedical Energy Harvesting and Charge Detection
Abstract: The increasing demand for intelligent biomedical monitoring systems has accelerated research into ultra-low-power sensing technologies capable of operating with high sensitivity and minimal energy consumption. Conductive polymers have attracted considerable attention for biomedical and nanoelectronic applications due to their tunable electrical properties, biocompatibility, and environmental stability. Among them, Polypyrrole (PPy) is a promising functional polymer that can enhance charge transport and electrostatic coupling in nanoscale devices. In this work, a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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An Efficient Method of Fault Analysis using Artificial Neural Network
Abstract: In the power system, there are many techniques to identify and classify the faults. So, it is utmost important to choose the suitable technique. In this paper, a novel technique based on ANN have been proposed. When abnormal conditions occur in the system, the purposed method identifies and classify the fault to protect the system from the faults and stop from the big hazards. Simulation of purposed Simulink model have …
Published in Current Trends in Signal Processing Read article
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Real-time Facial Recognition with Convolutional Neural Networks for Personalized Music Therapy
Abstract: In this project, a web-based application has been developed that integrates computer vision-based facial recognition, multiple algorithms, and machine learning approaches. The given system obtains a user’s emotions in the real-time frame by analyzing facial expressions such as eyes, mouth, the forehead, and so on. It detects emotions like happiness, sadness, that is neutrality, or rock. For a given detected emotion, language, and a user’s chosen artist, the system recommends …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 67–76 Read article
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An Efficient Method of Fault Analysis using Artificial Neural Network
Abstract: In the power system, there are many techniques to identify and classify the faults. So, it is utmost important to choose the suitable technique. In this paper, a novel technique based on ANN have been proposed. When abnormal conditions occur in the system, the purposed method identifies and classify the fault to protect the system from the faults and stop from the big hazards. Simulation of purposed Simulink model have …
Published in Current Trends in Signal Processing · Vol. 11, Issue 1, 2021 · pp. 9–25 Read article
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A Study of Diabetic Retinopathy using Convolutional Neural Networks
Abstract: This paper focuses on study of rapid detection of retinopathy, since prompt therapy can help decrease as well as possibly eliminate loss of eyesight. Furthermore, automatically locating portions of the optic picture which may include lesions could aid professionals in their identification function. Retinopathy is a frequent diabetic condition that comprises changes in the retinal blood capillaries. Such changes may lead capillaries to rupture as well as release fluid, causing …
Published in Journal of Instrumentation Technology & Innovations · Vol. 12, Issue 2, 2022 · pp. 1–6 Read article
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Performance of Smes Unit on Artificial Neural Network Based Multi-Area Agc Scheme
Abstract: The main objective of this paper is to develop Fuzzy controller to analyse the performance ofinstantaneous real active and reactive power (p–q) control strategy for extracting reference currents ofshunt active filters under balanced, un-balanced and balanced non-sinusoidal conditions. When the supplyvoltages are balanced and sinusoidal, the all control strategies are converge to the same compensationcharacteristics; However, the supply voltages are distorted and/or un-balanced sinusoidal, these controlstrategies result in different degrees …
Published in Journal of Power Electronics and Power Systems · Vol. 1, Issue 1-2-3, 2011 · pp. 47–58 Read article
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Early Warning Flood Forecasting Using Long Short-Term Memory Network
Abstract: AbstractFlooding is the natural disaster which leads to massive loss of life and property as well. India faces this situation every year and millions of people are being displaced due to loss of shelter. Early warning of flood disaster in corresponding locality provides sufficient time to protect their precious life and property. However, the range of flood prediction introduces the issue of cost, reliability and maintenance. We are proposing the …
Published in Current Trends in Information Technology · Vol. 10, Issue 3, 2020 · pp. 30–34 Read article
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A Hybrid voice identification System with Fuzzy Technique and ART2 Neural Network on BPF Technique
Abstract: Abstract:In this work, we evaluate the performance of voice identification through the hybrid method using fuzzy and Adaptive Resonance Theory2. The Voice identification is an important task, which shows the active interaction of natural human-machine, for over last important two decades. The objective of this work, it is consists in working out an identification rate of voice identification. The proposed methodology presented allows evaluating the identification process which considers a …
Published in Journal of Communication Engineering & Systems · Vol. 8, Issue 3, 2018 · pp. 1–6 Read article
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Performance Analysis of FIR Digital Filter using Artificial Neural Network for ECG Signal
Abstract: AbstractIn performance of electrocardiography (ECG) signal, signal acquisition must be noise free. This paper deals with the application of the digital finite impulse response (FIR) filter on the raw ECG signal. In this paper different window techniques used to design FIR filter and their signal to noise ratio are compared. The dataset configured for multilayer perceptron (MLP) training with feed forward algorithm. Finally the MLP is trained and the results …
Published in Journal of Communication Engineering & Systems · Vol. 3, Issue 2, 2013 · pp. 28–32 Read article
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Email Spam Classifications Based on Support Vector Machine and Recurrent Neural Network
Abstract: In recent times, e-mail has become one of the fastest and the utmost economical process of communication. Spam emails have dramatically increased over the past few years as a result of the growth in email subscribers. In this growing world, most of the transactions, business, study materials are taking place through emails. But due to the social networks and advertising, some of the emails contain undesirable information known as spam. …
Published in Journal Of Network security · Vol. 10, Issue 2, 2022 · pp. 14–18 Read article
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Neuro-Fuzzy Control Systems: A Cross-Domain Review
Abstract: This paper presents a comprehensive review of the application of neuro-fuzzy control systems in various industries. Using the combined strengths of neural networks and fuzzy logic, neural-fuzzy control systems emerge as versatile tools to solve challenging control challenges It begins with clarifying the theoretical basis of neural fuzzy systems, and emphasizing their scalability, definition, and robustness. Specific examples in each domain highlight the effectiveness of neuro-fuzzy control in solving real …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 1, 2024 · pp. 29–38 Read article
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An Abnormal Expression Detection System (AEDS) Using Deep Learning Algorithms
Abstract: In the last decade, many deep learning algorithms have achieved remarkable success and gained popularity in various computer vision tasks, including object detection, image recognition, and segmentation. This AEDS (Abnormal Expression Detection System)leverages the power of deep learning algorithms to detect abnormal facial expressions in real-time automatically. AEDS proposed two important models; those are Deep CNN and RNN. CNN is responsible for learning discriminative features from facial images and capturing …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 72–79 Read article