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298 articles for “multi-class classification”
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Immune Dysregulation and Cytokine Circuitry in Genital Endometriosis: Mechanistic Insights and Next-Generation Immunotherapeutic Strategies
Abstract: Genital endometriosis is increasingly recognized as an immune-mediated inflammatory disorder driven by complex interactions between dysregulated immune cells, cytokine hubs, and microbiome-derived modulators. This review introduces a novel “immune–cytokine circuitry” framework that unifies innate and adaptive immune abnormalities with key cytokine loops sustaining chronic inflammation, angiogenesis, neuroinflammation, and immune tolerance. Within this circuitry, macrophage polarization, dendritic cell immaturity, NK-cell anergy, Treg expansion, Th17 amplification, and B-cell–mediated autoimmunity converge to establish …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 1, 2026 · pp. 06–16 Read article
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Performance Evaluation of Direction of Arrival Estimation in Smart Antenna
Abstract: Direction of arrival (DOA) estimation has typically played a key role in signal processing. Its task is to find the directions impinging on an array antenna to increase the performance of the received signal. To use DOA estimation methods that are applicable to most environments has become the key of technique implementation. The traditional algorithms can get superior performance for DOA estimation in the rich receiving conditions, but they are …
Published in Current Trends in Signal Processing · Vol. 6, Issue 3, 2016 · pp. 39–48 Read article
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Direction of Arrival Estimation in Mobile Communication Systems using MUSIC Algorithm
Abstract: AbstractAdaptive antenna arrays use multiple antenna elements to form directional patterns in order to improve the performance of wireless communication systems. The antenna arrays also have the ability to estimate the Direction-of-Arrival (DoA) of the signals received from the desired transmitters as well as the directions of interference signals. The results of DoA estimation are then used to adjust the weights of the adaptive Multi-Input Multi-Output (MIMO) antenna so that …
Published in Journal of Communication Engineering & Systems · Vol. 3, Issue 2, 2013 · pp. 20–27 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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AIS-MACA- Z: MACA based Clonal Classifier for Splicing Site, Protein Coding and Promoter Region Identification in Eukaryotes
Abstract: Bioinformatics incorporates information regarding biological data storage, accessing mechanisms and presentation of characteristics within this data. Most of the problems in bioinformatics and be addressed efficiently by computer techniques. This paper aims at building a classifier based on Multiple Attractor Cellular Automata (MACA) which uses fuzzy logic with version Z to predict splicing site, protein coding and promoter region identification in eukaryotes. It is strengthened with an artificial immune system …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 1, Issue 1, 2014 · pp. 1–6 Read article
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Effect of Image Band Number and Band Multicollinearity on Mapping Accuracy of Tree Diversity and Evenness
Abstract: 800x600 Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 Satellite imageries are increasingly being used in the studies of plant diversity due to cost effective wider spatial coverage. Multispectral or hyperspectral imageries consist of different spectral bands where some bands might be multicollineared among them and deemed redundant to use in the classification/analysis. This study investigates how the accuracies of maps of tree diversity and evenness of an area …
Published in Journal of Remote Sensing & GIS · Vol. 4, Issue 2, 2013 · pp. 14–22 Read article
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Enhancing Road Safety with the Latest Breakthrough: Real-time Vehicle Classification, Counting, and Speed Estimation Using YOLOv8n and Deep SORT Algorithm
Abstract: The real-time vehicle classification, counting, and speed estimation system based on YOLOv8n is an important tool for monitoring traffic flow on highways. However, because they are distinct objects from their surroundings, it is still difficult to detect them, which has an impact on how accurate vehicle counts are. To tackle this concern, this paper suggests the implementation of a vision-centric system for real-time vehicle monitoring and identification. The approach involves …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 12, Issue 1, 2024 · pp. 10–18 Read article
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Evaluation of Industry 4.0 Adoption Obstacles Through the Use of SMEs
Abstract: Industry 4.0 offers significant technology advancements, but businesses must overcome several obstacles before implementing it. Although a lot of work has gone into identifying the hurdles that most businesses face, the literature currently in publication has not taken the time to examine how these barriers relate to one another or what that means for practitioners. Within the framework of Portugal's manufacturing sector, we employ the interpretative structural modelling (ISM) technique …
Published in Journal of Production Research & Management · Vol. 13, Issue 3, 2023 · pp. 24–38 Read article
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Study of Cascaded H Bridge Multilevel Inverter
Abstract: The inverters are now-a-days used broadly. Inverters are classified as two level inverters and multilevel inverters. There are too many limitations; conventional inverters at high power and high voltage applications. So, multilevel inverters become useful for high power and high voltage applications due to their increased number of levels at the output voltage. The harmonics are reduced by increasing the number of levels and output voltage has a tendency to-end-up …
Published in Journal of Power Electronics and Power Systems · Vol. 6, Issue 1, 2016 · pp. 45–54 Read article
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EMOTION RECOGNITION FROM ELECTROENCEPHALOGRAM SIGNAL AND EYE MOVEMENT BASED ON DEEP LEARNING
Abstract: Emotion recognition from electroencephalogram (EEG) signals has gained significant attention due to its potential in human- computer interaction (HCI), mental health monitoring, and personalized content delivery. This paper presents the use of Convolutional neural networks (CNNs) to classify emotions such as happiness, sadness, fear, neutral, and disgust by leveraging a fusion of EEG signals and eye movements data. Compared to conventional methods of emotion detection, such as those that rely …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 8–15 Read article
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Automated Machine Learning System for Model Selection and Hyperparameter Optimization
Abstract: The proliferation of machine learning applications in various scientific and industrial domains has given rise to an urgent need for developing principled, automated techniques for optimal architecture selection and hyperparameter tuning for machine learning models without human expert intervention. In this paper, we introduce the Automated Machine Learning System for Model selection and hyperparameter Optimization (AMLSMO)—a state-of-the-art, all-encompassing AutoML system that combines the power of meta-learning-based warm-starting, Bayesian Optimization with …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 15–23 Read article
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Path Lab-AI: An Autonomous Framework for Error-Free Histopathology Slide Interpretation
Abstract: Path Lab-AI represents a fully autonomous platform for the analysis of histopathology slides with circumscribed structures, designed to obtain highly accurate results using diagnostic methods and avoiding the usual limitations of standard microscopy-based pathology. Leveraging recent deep learning and whole slide image (WSI) analysis innovations, our system takes advantage of automated WSI ingestion along with pre-processing steps to account for staining variability, remove artifacts, and localize tissue from background. Such …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 19–30 Read article
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Data Stream Mining
Abstract: A data stream can be considered as an ordered sequence of data items, where the elements of the series continuously arrive as time progresses. Data stream mining is the procedure of extracting knowledge structures from such continuous, rapid data records. Mining data streams nurtures new problems for the data mining community regarding how to mine continuous high-speed data items that you can only have one look at. Due to this …
Published in Recent Trends in Programming languages · Vol. 5, Issue 1, 2018 · pp. 1–5 Read article
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Modified Optical Flow Morphology for Multiple-Object Tracking with Autonomous Driving Applications
Abstract: In this study we have presented a real-time applicable multiple object tracking algorithm for autonomous driving applications. The proposed method is based on the modified morphology of the optical flow technique. Here the method allows the non-prior training of optical flow constraints for the detection of the objects. Additionally, it let the system execute itself in parallel rather than those sequential computing object tracking algorithms giving huge computing time for …
Published in Journal of Advancements in Robotics · Vol. 2, Issue 1, 2015 · pp. 1–7 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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Skin Disease prediction and classification from dermoscopy images using Neural Network
Abstract: Skin diseases are among the most common health-related problems affecting people of all age groups, and their occurrence often varies with seasonal and environmental conditions. Delayed or incorrect diagnosis of skin disorders can lead to severe complications, making early and accurate detection extremely important for effective treatment and prevention. In recent years, rapid advancements in deep learning and neural network technologies have significantly contributed to the development of automated medical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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Local Binary Pattern-based Noise Robust Feature for Texture Classification
Abstract: Abstract: The presence of noise degrades the local binary pattern-based classification efficiency. In the present work, a modified local binary pattern ( —modified noise robust local binary pattern) based classification is proposed. In this, a local binary pattern-based feature is modified, which also captures macrostructure information, whereas the existing features capture microstructure texture information only. The new feature is tested on Outex_TC_00010, Outex_TC_00012 and Brodatz datasets for rotation invariant and …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 6, Issue 3, 2019 · pp. 31–47 Read article
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Fault Detection in Solar PV Systems Integrated with the Power Grid: Evaluating Logistic Regression through Confusion Matrix Analysis
Abstract: This paper proposes a method for failure detection in grid-integrated solar photovoltaic (PV) systems using logistic regression and real-time sensor data. The approach effectively classifies and identifies seven distinct fault types. The developed model demonstrates a high fault identification accuracy, ranging from 93% to 96.5% across various fault types and operational conditions. By leveraging logistic regression, the system utilizes key independent variables that significantly influence the classification process. Additionally, the …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 2, 2025 · pp. 45–52 Read article
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A Comparison Study of Different Classification Algorithm on Brain Tumor Segmentation
Abstract: A brain tumor is a tissue mass caused by aberrant cell proliferation in the brain. It is a collection of tissues that causes hormonal alterations and eventually death. In order to save human lives, brain tumors prognosis and prevention is a difficult task. The use of modern medical image processing approaches has made the identification of brain tumors more flexible in recent years. Due to the absence of ionizing radiations, …
Published in Trends in Opto-electro & Optical Communication · Vol. 11, Issue 3, 2021 · pp. 1–7 Read article
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A Dual-Model Deep Learning Framework for Early Alzheimer’s Detection Using Clinical Data and Neuroimaging with Architectural Performance Analysis
Abstract: Alzheimer’s disease (AD) poses a significant global health challenge due to its increasing prevalence and the absence of definitive cures. Early diagnosis is crucial for effective intervention and management. This study presents a dual-model deep learning framework for the early detection and classification of AD using both structured clinical data and neuroimaging datasets. Model 1 utilizes a greedy layer-wise autoencoder approach applied to structured data, achieving optimal binary classification accuracy …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 1–12 Read article