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54 articles for “classification algorithm”
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Face and Speech Emotion Recognition
Abstract: The study “faces and speech recognition” underscores the critical role of speech emotion recognition (SER) and its diverse applications across various fields, such as medicine, human-computer interaction, and customer service. SER has gained significant importance in cognitive psychology due to its potential to enhance user experience, improve patient care, and optimize the interaction between users and products. The process involves the identification and extraction of essential features from speech signals, …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 2, 2024 · pp. 35–43 Read article
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Review of Feature Selection Methods and Semi Supervised Feature Selection Algorithms for Classification
Abstract: Current evolution in technology has resulted in tremendous growth of data with respect to dimensionality and sample size. Knowledge discovery from these high dimensional data are becoming cumbersome. Though powerful machine learning algorithms are prevalent, noisy data, imperfect sensing and collection of data leads to poor and defective knowledge discovery. Noise and redundant features cannot be circumvented due to which data collection process is biased. Dimensionality reduction techniques namely feature …
Published in International Journal of Software Computing and Testing · Vol. 6, Issue 1, 2020 · pp. 39–51 Read article
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Breast Tumor Classification Using Machine Learning Algorithm
Abstract: Breast cancer is characterized by genetic mutations, periodic pain, changes in the length, color (redness) and texture of the breast skin. The categories of most types of breast cancer led the pathologist to a systematic and objective prognostic analysis. In general, the most common category is binary (benign/malignant). Today, Learning Gadget (ML) strategies are widely used in breast cancer classification problems. Offers extreme accuracy and powerful diagnostic technology. It kills …
Published in International Journal of Microwave Engineering and Technology · Vol. 8, Issue 1, 2022 · pp. 35–40 Read article
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Review on GABASS (Genetic Algorithm Based Attributes Subset Selection) Using Naïve Bayes Classifier
Abstract: ABSTRACT In the present work, review on Genetic Algorithm based Attributes Subset Selection using Naïve Bayes Classifier is presented. A dataset can contain a few components. Many clustering strategies are intended for grouping low-dimensional information. In highdimensional space discovering groups of information objects is trying because of the scourge of dimensionality. At the point when the dimensionality expands, information in the immaterial measurements may create much commotion and veil the …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 4, Issue 2, 2018 · pp. 21–27 Read article
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Classification of power quality disturbances using advanced deep learning algorithms for Accurate and efficient electrical signal analysis
Abstract: Power systems today have to deal with more and more power quality issues (PQDs) like voltage drops, rises, harmonics, and transients because more people are using renewable energy sources and electronic devices. These problems can hurt equipment, stop services, and lower the overall reliability of power. In real-time settings, traditional detection methods often don't work as quickly or accurately as they should. This paper looks at how deep learning models, …
Published in International Journal of Power Electronics Controllers and Converters · Vol. 12, Issue 2, 2026 Read article
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System for Predicting and Recommending Placement on Campus
Abstract: The campus placement system uses classification algorithms like decision trees, random forests, support vector classifiers, and logistic regression to estimate the likelihood that an undergraduate student will be hired by a business. The placement prediction method assists in identifying students’ needs and the areas in which they fall short, allowing students to strengthen their profiles and increase their chances of being placed. The placement predictor uses a number of parameters …
Published in International Journal of Distributed Computing and Technology · Vol. 9, Issue 1, 2023 · pp. 18–25 Read article
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Blood Cell Subtype Classification Using Deep Learning
Abstract: A vital component of human bodies is blood. Despite making up only 1% of the human body, blood cells have a greater impact on disease and infection detection. These blood cell subtype classifications also aid in ensuring that patients receive the quickest-acting medical treatment and recover swiftly. To get the findings, many machine learning techniques are used, including the Feature Extraction methods (K* classifier and Decision table) and the Image …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 9, Issue 1, 2023 · pp. 37–45 Read article
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Brain Tumor Detection using Machine Learning Methods-KNN, SVM, DT, RF
Abstract: Brain tumor is a major contributor to illness and death worldwide, and timely diagnosis is essential for successful treatment and improved outcomes Recent research has looked into the possibility of machine learning algorithms for detecting and classifying brain tumours in medical pictures. In this study, four commonly used machine learning algorithms (K-Nearest Neighbours, Decision Trees, Support Vector Machines, and Random Forests) were evaluated for their effectiveness in brain tumor detection. …
Published in International Journal of Chemical Engineering and Processing · Vol. 9, Issue 2, 2023 · pp. 48–59 Read article
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Design and Implementation of Autonomous Robots for Crack Detection in Dam Walls: Analyzing Vision-Based Algorithms and Structural Health Monitoring
Abstract: AbstractThe maintenance of dam walls is critical to ensure structural integrity, safety, and efficient water management. Cracks and other structural deficiencies can lead to severe consequences if left undetected. Traditional inspection methods are labor-intensive, time-consuming, and often hazardous, necessitating the development of autonomous systems for effective monitoring. This study focuses on the design and implementation of autonomous robots equipped for crack detection in dam walls, with an emphasis on vision-based …
Published in International Journal of Structural Mechanics and Finite Elements · Vol. 11, Issue 1, 2025 · pp. 14–26 Read article
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Use of Natural Language Processing for Hate Speech Detection on SocialMedia:
Abstract: The exponential growth of social media platforms has led to an increase in user- generated content, enhancing global connectivity but also facilitating the spread of harmful language, including hate speech. Addressing this issue requires robust, Naïve Bayes, Decision Tree, K-Nearest Neighbours (KNN), Linear Regression, and Random Forest—were tested, with Linear Regression achieving the highest accuracy automated systems for detecting and mitigating offensive content. This paper presents a comprehensive analysis of …
Published in International Journal of Digital Communication and Analog Signals · Vol. 11, Issue 2, 2025 · pp. 9–16 Read article
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A Review of Modeling and Data Mining Techniques Applied for Analyzing Steel Bridges
Abstract: The vibration response data measured from the structure contains uncertainties and requires different techniques for its analysis. The present study involves the comprehensive review of the model based and data mining techniques which are frequently applied by various researchers in past to solve various multi criteria decision making and analysis problems. The selection of suitable technique for specific problem is required to obtain accurate outcomes. The literature survey is done …
Published in International Journal of Software Computing and Testing · Vol. 7, Issue 1, 2021 · pp. 1–15 Read article
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Climate Change Modeling Using Machine Learning and Big Data
Abstract: Climate change is now one of the biggest issues that affect the world today and studying its impacts for it is very significant in enabling the formulation of social policies. This paper also discusses how climate sciences, machine learning, and big data analytics can greatly help in the improvement of the current capacities in climate modeling. Explaining the methods of climate modeling, we look at how the big data offers …
Published in International Journal of Software Computing and Testing · Vol. 11, Issue 1, 2025 · pp. 6–11 Read article
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Identifying Fake News Using Big Data
Abstract: In today's world, where digital information spreads swiftly, the rise of fake news poses a threat to society. This research paper presents a method to address this issue by employing data analytics. To address the issues of misinformation, public manipulation, and threats to democracy we propose a framework. Our strategy incorporates advanced methodologies, including natural language processing, machine learning, and network analysis. Using these techniques, we examine various data sources …
Published in International Journal of Distributed Computing and Technology · Vol. 10, Issue 1, 2024 · pp. 7–14 Read article
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Support Vector Machine-based Flower Image Classification for Commercial Applications
Abstract: Flowers are crucial raw materials in many industries, including pharmaceuticals and cosmetics. Classifying flowers manually is time-consuming, inconsistent, and requires professional judgment from a botanist. Computer-aided flower classification is a promising approach to this problem. Image classification often employs support vector machines (SVMs) as widely favored algorithms. This study evaluated the performance of SVMs for flower image classification. The results showed that SVMs can achieve good accuracy on this task, …
Published in International Journal of Software Computing and Testing · Vol. 9, Issue 2, 2023 · pp. 44–53 Read article
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A Comprehensive Study of Fault Diagnostics of Roller Bearings Using Continuous Wavelet Transform
Abstract: One of the prominent causes of breakdown of rotating machinery, bearing failure, proves to be costly to the industry. Unexpected machine stoppage disrupts production schedule and maintenance strategies. Therefore, condition monitoring has become a very important research field in recent years. It can be used to avoid unexpected failures of critical systems. Bearing fault diagnostics using vibration signals has proven to be very effective. This paper deals with the fault …
Published in International Journal of Manufacturing and Materials Processing · Vol. 2, Issue 2, 2016 · pp. 36–55 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 (or CNNs) and Haar Cascade classifiers. The suggested method uses CNN to recognize facial expressions and Haar Cascade algorithm for face detection. The methodology begins with preliminary processing the input photos, followed by face detection …
Published in International Journal of Microwave Engineering and Technology · Vol. 10, Issue 2, 2024 · pp. 41–50 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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Analysis of EEG Signal for Brain Computer Interface
Abstract: Brain-computer interface (BCI) frameworks causes a subject to issue commands to an electronic device just by methods for brain activity. EEG has wide applications in the brain-computer interface (BCI) systems. Sadly, the spatial resolution of EEG is very low, because of the volume conduction. While measuring signals related to motor movements various artefacts also get added. We have studied pre-processing techniques and classification techniques which improve performance. While there are …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 6, Issue 2, 2020 · pp. 6–11 Read article
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Application of Surface Water Quality Classification Models Using Principal Components Analysis and Cluster Analysis
Abstract: Water quality monitoring has one of the highest priorities in surface water protection policy. Many variety approaches are being used to interpret and analyze the concealed variables that determine the variance of observed water quality of various source points. A considerable proportion of these approaches are mainly based on statistical methods, multivariate statistical techniques in particular. In the present study, the use of multivariate techniques is required to reduce the …
Published in International Journal of Water Resources Engineering · Vol. 5, Issue 1, 2019 · pp. 19–31 Read article
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A Review on Design and Analysis Model for Detectionand Classification of Lung Diseases Using Medical Images
Abstract: A key component of the human respiratory system, the lung regulates blood oxygen levels through gasexchange. Diseases linked to the lungs are becoming more common as pollution levels rise. In order topreserve human life, it is crucial to identify lung disorders early. In order to forecast lung disease, clinicalprofessionals analyze medical imaging, such as CT or X-rays. Clinicians identify lung disease by applyingtheir medical expertise and knowledge. Because expert knowledge …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 2, 2025 Read article