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415 articles for “neural network method”
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An Analysis of Machine Learning Models for Early Cardiac Risk Stratification
Abstract: The paper shows an in-depth study of machine learning and artificial intelligence solutions to early cardiac risk stratification which has a crucial necessity because cardiovascular disease (CVD) prediction remains a significant issue that needs to be improved beyond the conventional risk score. Since CVD is the most serious disease killer in the world, claiming 17.9 million deaths every year, there is a strong need to get the most sophisticated predictive …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Monitoring and Modeling of Atmospheric Change Indices In Parts of Imo State Using GIS, MATLAB and ANN
Abstract: Geographic Information System (GIS) and Matrix Laboratory (MATLAB) Models were used to study air quality in parts of Imo State. Primary data were obtained by conducting relevant analysis using standard instrumental methods on open-air rainwater samples collected in the dry and the rainy seasons for two consecutive years. GIS showed that the pollutants were present throughout the year. Artificial Neural Network (ANN) of MATLAB 2015 was used to represent data …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 15, Issue 1, 2024 · pp. 25–74 Read article
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Energy-efficient Image Classification on Edge Devices: Implementation and Evaluation
Abstract: Image classification is a computer vision problem where an algorithm determines a class or label for a given image. Various real-time applications like object recognition, medical diagnosis, person recognition, etc. Image classification property on edge devices is useful for autonomous vehicles, surveillance, and healthcare and internet of things deployments. The advancement of deep learning based methods and graphics processing units (GPU) devices allows efficient processing locally. The study utilizes a …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 10–18 Read article
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Early Alzheimer's Disease Detection Using Deep Ensemble Learning and MRI Image Analysis
Abstract: Early detection of Alzheimer's disease (AD) is crucial to slowing cognitive decline and enabling timely clinical interventions. Traditional diagnostic methods, including cognitive tests and single-model classifiers, have limited sensitivity during early stages of the disease. This paper presents a deep ensemble learning approach that integrates multiple convolutional neural networks (CNNs) for accurate Alzheimer's disease detection using structural Magnetic Resonance Imaging (MRI) data. The proposed framework utilizes ResNet50, VGG16, and DenseNet121 …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 1–9 Read article
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An Integrated Simulation Framework for Predicting Dielectric Breakdown and Electrical Aging in Epoxy-Silica Composite Insulation Systems
Abstract: This paper provides a combined computation approach in forecasting the dielectric breakdown and electrical aging within epoxy-silica composite of insulation system. The approach will consist of a three-complementary methodology (a combination of computing electric field using the finite element analysis, estimation of the probability of failures or breakdowns using Weibull statistics, and prediction of degradation tendencies using artificial neural networks). The epoxy-silica composites are of 10-40 volumes fillers. The simulations …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 339–376 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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Power Quality Monitoring in Wind Solar Hybrid System
Abstract: With the development of new functionalities, solar and wind energy based hybrid systems are upcoming energy source with higher efficiency. Solar and wind energy being naturally available in abundance and non-polluting, is one of the most promising sources. Due to the development of modern power electronic devices, the power quality of wind solar hybrid system gets affected. Hence, due to the increasing usage of sensitive electronic equipments in wind solar …
Published in Journal of Power Electronics and Power Systems · Vol. 8, Issue 1, 2018 · pp. 16–23 Read article
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Development of a Soft Computing-Based Island Detection System and Performance Analysis
Abstract: There has been an overestimation of the global energy consumption in the last few years. Distributed Generators are being propelled forward by the motivation provided by the absence of suitable transmission capacity, exaggerated transmission and distribution mishaps, and the release of power marketing (DGs). It's a distributed age unit (DG slash hack expansion) and regional units linked to distribution that power the system, which has yet to have hundreds of …
Published in Journal of Semiconductor Devices and Circuits · Vol. 8, Issue 3, 2021 · pp. 1–15 Read article
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Machine Learning Based Approaches for the Detection and Classification of Crop Leaf Diseases
Abstract: Crop leaf diseases pose a significant threat to agricultural productivity worldwide, leading to substantial crop losses and economic consequences. Timely and precise identification and categorization of these diseases are vital for effective disease management and safeguarding crops. Over the past years, machine learning methods have gained prominence due to their potential to automate disease diagnosis and classification procedures. This review paper presents an overview of the various machine learning based …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 2, 2023 · pp. 31–38 Read article
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A Machine Learning-based Analysis of Climate Change
Abstract: Climatic variations are a pressing global challenge that demands immediate and comprehensive attention. A wealth of articles has been published on climate change mitigation and adaptation, yet there remains a need for innovative methods to explore the complexities of climatic variations and to devise more efficient and effective strategies for adjustment and alleviation. With technological advancements, machine learning (ML) and deep learning (DL) approaches have derived significant popularity across various …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 1–10 Read article
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Detection of Phishing Website Using URL
Abstract: Phishing attacks are one of the greatest threats to online security, where fraud websites deceive users into giving out sensitive information. Traditional methods of detection, such as blacklists and heuristic-based systems, often fail in identifying newly created or sophisticated phishing websites. This study proposes an intelligent phishing website detection system using Convolutional Neural Networks (CNNs) in analyzing URLs and associated features. Using labeled URLs, the system employs such attributes such …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 10–15 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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Review of Deep Learning in Medical Imaging
Abstract: In the past few years, computer-aided analysis has fallen quickly behind. Organ categorization and segmentation is a key stage in computer-aided diagnosis. In recent years, there has been a lot of interest in the division of abdominal organs such as the liver, stomach, kidney, pancreas, and bladder from various picture modalities. Radiologists or medical specialists analyze abdominal pictures the majority of the time. Due to subjectivity, intricacy of the picture, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 9, Issue 3, 2022 · pp. 16–24 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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Methods Based on Machine Learning for Large-scale Classification of Crop Leaf Diseases
Abstract: Worldwide productivity of crops is seriously threatened by crop leaf diseases, which can result in large crop losses and negative economic effects. Effective disease management and crop protection depend on the early and precise detection and classification of these illnesses. Machine learning approaches have gained popularity recently due to their ability to automate procedures related to illness diagnosis and classification. An overview of the several machine learning–based methods used for …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 1, 2024 · pp. 11–23 Read article
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AbhiGyam: A Machine Learning Model-driven Research Platform for Assessing Accessibility Infrastructure in Indian Cities
Abstract: This work presents AbhiGyam, a machine learning-driven research platform designed to streamline and automate the assessment of accessibility infrastructure in Indian cities. AbhiGyam leverages the Google Maps API to transmit street view images to the backend, where computer vision techniques are implemented using OpenAI's CLIP (Contrastive Language-Image Pre-training) model to identify objects such as ramps, sidewalks, crosswalks, and parking spaces. The accuracy of the model is validated using labeled data …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 84–91 Read article
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Statistical Models for Predicting Genetic Variability and Disease Susceptibility
Abstract: Differences in genetics are key to understanding why some individuals are more prone to certain diseases than others. Recent advancements in genomic research, combined with statistical modeling techniques, have made significant strides in predicting disease risk based on genetic factors. This review explores the application of statistical models for predicting genetic variability and their role in disease susceptibility. We discuss traditional methods like linear regression and genome-wide association studies (GWAS), …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 30–34 Read article
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Tensor-Flow Based Approach to Identify Author of the Text
Abstract: Now-a-days a lot of content is available on internet, and people upload lot of information in form of opinion, review, description, recipe etc. online. In such scenario to trace the authenticity of the data, it is necessary to develop an author identification system. It has become a difficult problem in the scope of unnamed information has increased with fast growing Internet life. It is a process to identify author of …
Published in Current Trends in Information Technology · Vol. 8, Issue 3, 2018 · pp. 23–29 Read article
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A study in Leveraging Deep Learning and IoT Arrays for Dynamic, Hyper-Local Atmospheric Intelligence
Abstract: The critical demand for high-resolution, actionable atmospheric data is challenged by the high cost and sparse coverage of traditional regulatory monitoring stations. This paper explores the synergistic paradigm shift enabled by integrating low-cost, dense Internet of Things (IoT) sensor arrays with advanced Artificial Intelligence (AI) methodologies, specifically Deep Learning (DL) models. We address the primary limitations of low-cost sensors—inherent bias, sensitivity to environmental drift (temperature/humidity), and calibration inconsistency—by utilizing AI …
Published in International Journal of Atmosphere · Vol. 2, Issue 2, 2025 · pp. 50–62 Read article
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Mode Choice Analysis: Fundamental and Models
Abstract: AbstractTravel behavior plays an important role in transportation planning. Mode choice has direct impact on the policy making decision. It is behavioral and complex in nature. The objective of this study is to carryout detailed review on various modeling methods of mode choice analysis. The factors that affect the traveler’s mode choice decision have been discussed. The methods of data collection have been briefly discussed. Further the paper highlights on …
Published in Trends in Transport Engineering and Applications · Vol. 5, Issue 1, 2018 · pp. 7–13 Read article