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31 articles for “SVM”
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Performance Analysis of SVM and CNN Networks for Defect Detection in Solar Panel
Abstract: Use of solar panel in generating electricity is increasing globally day by day to meet the increase in demand of power. Many developments have been made in order to achieve higher efficiency of the system. But efficiency of the system may still decrease due to harsh environmental conditions or poor handling of the. These factors highly contribute in the performance degradation of the system. For detection of these irregularities, human …
Published in International Journal of Analog Integrated Circuits · Vol. 7, Issue 1, 2021 · pp. 15–24 Read article
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Identifying the Age Using Face Image Using DWT, LBP, SVM and k-NN
Abstract: ABSTRACTThe research related to identifying the age using face images has become progressively more important, due to the fact it has a multiplicity of potentially helpful applications. In this paper we survey the complete age synthesis or age estimation from face images techniques. Automatic facial age identifying is one of the main issues in pattern recognition which shows the age of human according to her/his facial expressions. Basically, age detection/estimation …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 6, Issue 2, 2020 · pp. 26–37 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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Predictive Models for Drinking Water Quality: Leveraging Machine Learning for Improved Safety and Efficiency
Abstract: Quality of drinking water is one of the critical determinants of public health, leading to severe environmental and health-related issues when poor. The paper examines the integration of machine learning techniques that could improve accuracy and efficiency in assessing drinking water quality. The traditional techniques of monitoring drinking water are resource-intensive yet lack timely insight into contamination events. In this scenario, an evaluation of the performance of ML models such …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 11, Issue 1, 2025 Read article
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Facial Recognition in Education: Revolutionizing Attendance Tracking for Enhanced Efficiency and Security
Abstract: The goal of this project is to develop a facial recognition-based attendance system for educational institutions to improve and modernize the current system and make it more effective and efficient than it was in the past. The distinctive features of the human face allow for individual identification. Since there is little chance of a face deviating or being duplicated, it is utilized to trace identification. The article also covers the …
Published in International Journal of Digital Communication and Analog Signals · Vol. 10, Issue 1, 2024 · pp. 1–6 Read article
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Object Detection Technique by Using Support Vector Machines
Abstract: We portray the FCNN-SVM classifier, which combines the help vector machine (SVM) approach and the speedy nearest neighbor development course of action administer (FCNN) with a particular ultimate objective to make SVMs rational on immense gatherings of data. As an essential responsibility, it is probably exhibited that, on huge and multidimensional instructive accumulations, the FCNN-SVM is a few solicitations of significance faster than SVM, and that the amount of help …
Published in International Journal of Distributed Computing and Technology · Vol. 4, Issue 2, 2018 · pp. 1–4 Read article
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Advancing Maize Leaf Disease Detection: A Machine Learning Approach
Abstract: Every day, countless grains and fruits are cultivated around the world. To keep up with the growing population’s needs, farmers are constantly adopting new and advanced techniques. Furthermore, the development and application of new technologies enable the quick and simple detection of plant diseases. Identifying plant diseases at an early stage is crucial to minimizing their effects on crop productivity and quality. Traditional diagnostic methods often rely on expert knowledge …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 1, 2025 · pp. 17–25 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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Estimation of Crop Yield Prediction Using Machine Learning Technique.
Abstract: Agriculture serves as the primary source of livelihood for a significant portion of India's population, but it faces a myriad of challenges, including climate variability, soil fertility issues, and reliance on traditional farming practices. To address these challenges, researchers are increasingly turning to machine learning (ML) methodologies to predict crop yields more accurately. Studies have delved into the effectiveness of various ML algorithms such as Random Forest, Gaussian Process Regression, …
Published in International Journal of Agrochemistry · Vol. 10, Issue 1, 2024 · pp. 7–12 Read article
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Performance Comparison of Handwritten Digit Recognition Using Machine Learning Techniques
Abstract: Handwritten pattern, character and digit recognition has always been the most demanding and interesting fields of image processing. The objective of this work is representing and demonstrating the algorithms which are used to recognize handwritten digits. Recognition of handwritten digits has always a bit complex, but it is mostly used in various day-to-day applications. In the task of recognition, the digits are not correctly or accurately scripted or written as …
Published in International Journal of Digital Communication and Analog Signals · Vol. 7, Issue 1, 2021 · pp. 9–18 Read article
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Hybrid Machine Learning and Deep Learning approach for Adaptive congestion control in 5G/6G Network
Abstract: The rapid growth of data traffic, fueled by emerging applications such as autonomous systems, augmented reality (AR), virtual reality (VR), and the Internet of Things (IoT), poses major challenges for modern communication networks. With the rollout of 5G and the continuous transition to 6G, sophisticated congestion control techniques are needed to satisfy the demanding requirements of massive machine-type communication (mMTC), ultra-reliable low-latency communication (URLLC), and improved mobile broadband (eMBB). Conventional …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 11, Issue 2, 2025 · pp. 1–8 Read article
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Review of Anomaly Detection Techniques in MANETs: AMachine Learning Approach to Intrusion Detection, Attack Prediction, and Routing Security
Abstract: Mobile Ad hoc Networks (MANETs) are decentralized, self-organizing networks that offer flexibility and scalability for a variety of applications. However, their dynamic topology and limited resources make them highly susceptible to security threats. Traditional security measures often struggle to address the complexities of evolving and sophisticated attacks within such networks. This paper reviews the role of machine learning (ML) techniques in enhancing anomaly detection capabilities in MANETs, focusing on their …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 2, 2026 · pp. 1–5 Read article
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Predictive Analytics in E-Learning: Enhancing Student Performance Through Machine Learning Models
Abstract: With the explosion of electronic devices and internet technologies in today’s world, the amount of data we store has grown massively. Data is simply information that has been organized in a way that makes it easy to share or work with. A potent technology that enables computers to learn from data without direct programming is machine learning, which we employ in our research. The focus of this study is on …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 10, Issue 2, 2024 · pp. 1–5 Read article
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Soft Computing Based Prediction of Ultimate Bearing Capacity of Footings Resting on Rock Masses
Abstract: The present study attempts to predict the ultimate bearing capacity of shallow foundations on rock masses using five different soft computing techniques namely i) random forest regression approach, ii) artificial neural networks, iii) support vector machine with polykernel, iv) support vector machine with (radial basis function) RBF kernel and v) M5P model tree. The ultimate bearing capacity was assumed to be dependent rock mass rating, unconfined compressive strength of rock, …
Published in International Journal of Geological and Geotechnical Engineering · Vol. 5, Issue 2, 2019 · pp. 1–14 Read article
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Detection of Leaf Diseases Using Image Processing Techniques
Abstract: Agricultural field plays a vital role in the earning to feed ever growing population. The productivity of the crop depends on pest attack, disease, weather, etc. The disease in plants will affect the production of crops. Detecting diseases in plants through visualization is a traditional method which is not relevant. We are focusing on reliable, fast and accurate detection method that can be done using image processing techniques to monitor …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 5, Issue 2, 2019 · pp. 14–19 Read article
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MRAC Based Speed Estimation of Three DTC Techniques for Three-phase Inverter Fed IPMSM Drive
Abstract: This paper aims to study three Direct Torque Control (DTC) techniques for an Interior Permanent Magnet Synchronous Machine (IPMSM) using Model Reference Adaptive Control (MRAC). In the conventional DTC technique using a look-up table, gate signals are given to the Inverter that drives IPMSM. Since it is a 6-sector scheme and the operation of the minimum number of voltage vectors, undesired torque and flux ripples are created. Hence the problem …
Published in International Journal of Electrical Power System and Technology · Vol. 9, Issue 2, 2023 · pp. 1–15 Read article
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Multi-class Fault Diagnosis of Rolling Element Bearing Based on Empirical Mode Decomposition and Entropy Features
Abstract: Rolling element bearings are one of the most commonly used machine elements in engineering industry. Fault detection and diagnosis of rolling element bearings is essential for prevention of malfunction and failure during operation. The present work deals with rolling element bearing fault diagnosis by using Support Vector Machine (SVM) and Artificial Neural Network (ANN). Four types of bearing conditions are considered in the present analysis: inner race fault (IR), outer …
Published in International Journal of Manufacturing and Materials Processing · Vol. 2, Issue 1, 2016 · pp. 01–10 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
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Forecasting Trends in the Stock Market by Using Deep Learning Approaches
Abstract: Accurately predicting stock market trends remains a significant challenge in the field of finance. Deep learning, a subset of machine learning, has emerged as a powerful tool for capturing complex relationships within data. What sets deep learning apart is its ability to handle vast amounts of data, recognize intricate features, and adapt to evolving patterns, all while uncovering hidden insights. At its core, deep learning uses artificial neural networks that …
Published in International Journal of Software Computing and Testing · Vol. 10, Issue 2, 2024 · pp. 22–30 Read article
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Algorithmic Approaches for Data Mining and Machine Learning
Abstract: ABSTRACTTrends and technology always innovative and comes with some new. Sometimes technologies are introduces in more user friendly environment. In such version of technology advancement are also incorporated. Data mining is a best widespread knowledge attainment approach for knowledge discovery. The naval trends Machine learning also have a big interfere of data mining. Infect most of the data mining algorithm and methods are utilized for machine learning with minor amendment …
Published in International Journal of Distributed Computing and Technology · Vol. 6, Issue 2, 2020 · pp. 24–29 Read article