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662 articles for “machine learning method”
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Machine Learning Pipelines: A Survey on Automation, Scalability, and Deployment Strategies
Abstract: Machine learning (ML) has become a critical enabler of intelligent applications across domains, requiring robust, efficient, and scalable deployment workflows. This review paper provides an in-depth overview of machine learning pipelines, emphasizing three key dimensions: automation, scalability, and deployment methodologies. It begins by exploring automation techniques that reduce manual effort in data ingestion, preprocessing, model selection, and hyperparameter tuning. Tools such as AutoML, TFX, and workflow orchestration platforms are examined …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 17–28 Read article
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An Innovative AI-Integrated Approach for Identifying the Tensile Robustness of Polymeric Materials
Abstract: Polymeric materials have so many applications and character similar to flexibility, robustness and lightweight nature they are essential to a large variety of industries. Though, it is difficult to establish their tensile robustness appropriately, particularly in a variety of environmental situation. Provide a recommended Artificial Intelligence (AI)-integrated method to decide the issues of rapidly ascertaining the tensile robustness of the polymeric material. Using machine learning (ML), this study, predicted and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 90–97 Read article
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Machine Learning Regression Based Approach for Prediction of the Ultimate Tensile Strength of Tungsten Inert Gas Welded Joints
Abstract: Many leaders in technology education have shown that the main difference between the technical design process and the process of engineering construction analysis and efficiency [1–3]. The engineering analysis phase of the construction process is where the mathematical and scientific models principles are used to help the designer predict the design results. The engineering feasibility phase process is a systematic process that uses structural elements and conditions to allow the …
Published in Trends in Machine design · Vol. 8, Issue 2, 2021 · pp. 1–10 Read article
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Redefining Efficiency: Big Data Science in Supply Chain Design and Management
Abstract: The combination of resources, tools, and applications in the field of supply chain management (SCM) is rapidly expanding, creating both opportunities and challenges. The term "big data" is commonly used to refer to the large and complex sets of data that are now available. These data are believed to have the potential to improve decision making and increase profitability. To effectively analyze and utilize these data, new methods of data …
Published in Journal of Production Research & Management · Vol. 13, Issue 1, 2023 · pp. 6–10 Read article
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Image Processing Techniques for Detecting and Classification of Leaf Diseases
Abstract: Plants are the way to make a living. From the factors of our daily life to breathing we are totally dependent on plants. Therefore, plant care must be proper. Plant diseases involve, of instance, algae, bacteria, and viruses. Several researchers have to classify plant diseases but it is time consuming to manually identify them. Image processing techniques are used to detect various diseases of the plant. There are several steps …
Published in Trends in Opto-electro & Optical Communication · Vol. 11, Issue 2, 2021 · pp. 1–6 Read article
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Crop Health Monitoring and Weed Detection Using Drone Technology
Abstract: In an agriculture-based economy like ours, farmers and their cultivation play a significant role. With the extension of agriculture to wider fields, manual interference to monitor and detect crop health is becoming more difficult. Unmanned aerial vehicles (UAVs) have become well-known and affordable technology for a variety of precision farm uses in recent years. Combining the capabilities of drone technology and machine learning/deep learning algorithms, we can monitor crop health …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 1, 2023 · pp. 1–8 Read article
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Hybrid DL-ML Approach for Android Malware Detection
Abstract: The widespread growth of Android malware has become a significant mobile security threat during the past few years thus requiring the development of strong detection solutions. The primary tool applied in this research for Android malware detection consists of app permissions. The main indicator in the dataset for identifying malicious and benign applications functions through displaying application permission information. The evaluation of particular permission relationships with malware behavior leads to …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 18–25 Read article
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Survey of Liver Disease Prediction Using Machine Learning
Abstract: Liver disease is one of the major causes of death in all over world that impacts the number of people around the world. Diagnosis of liver at early stages is crucial to reduce morality. As technology is growing in health care, machine learning significantly affects health care for predicting conditions at early stages. This study reviews the different approaches based on machine learning and deep learning to predict liver disease. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 30–38 Read article
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A Systematic Review for Heart Disease Prediction Using AIML Algorithms
Abstract: Cardiovascular diseases (CVDs), commonly known as heart diseases, have consistently held the position of being the primary global cause of mortality for many years. They are also the most serious illness in India and the rest of the world. So, a method that is reliable, accurate, and easy to use is needed to find these diseases early and start the right treatment. Using a variety of medical datasets, machine learning …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 3, 2023 · pp. 53–61 Read article
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Face Recognition Attendance System Using Local Binary Pattern Histogram Algorithm
Abstract: Maintaining accurate and tamper-proof attendance records in educational and corporate environments has long been a challenge due to the limitations of manual and biometric systems. This study introduces the development and deployment of a contactless, automated attendance system that utilizes facial recognition through the local binary pattern histogram (LBPH) algorithm. The primary goal is to offer a secure and efficient substitute for conventional attendance methods by harnessing the power of …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 29–34 Read article
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A Comprehensive Survey of Polymer Detection Techniques and Computer-Based Analysis Methods for Advanced Material Characterization
Abstract: Polymers are widely used in aerospace, automotive, biomedical, packaging, electronics, and manufacturing industries because of their lightweight nature, durability, and versatility. Accurate polymer identification and characterization are essential for quality control, recycling, performance assessment, and the development of advanced materials. Characterization helps determine important properties such as chemical composition, molecular structure, thermal stability, mechanical strength, and surface morphology, which influence material performance and application suitability. Traditional polymer detection methods include …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 921–929 Read article
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A Survey on Image Forgery Detection Techniques Using Machine Learning Approaches
Abstract: With the advent of newer technologies and usage of data in various service fields like education, commercial and healthcare, etc. The possibility of tampering and altering the data in the form of media like images is easily seen to derive various illegitimate benefits and outcomes. The rapid advancements in technology and the increased utilization of data in various service sectors such as education, commerce, healthcare, etc., have raised concerns about …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 10, Issue 2, 2023 · pp. 17–26 Read article
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IoT Sensors to Monitor Pipeline Pressure and Flow Rate Combined with ML-Algorithms to Detect Leakages
Abstract: In the field of fluid mechanics, pipelines are the lifeblood of industries, transporting everything from natural gas and oil to water and chemicals. Maintaining their integrity is paramount for safety, economic efficiency, and environmental protection. Traditional leak detection methods explained in fluid mechanics can be slow, expensive, and sometimes fail to identify small leaks early enough to prevent significant damage. However, the convergence of Internet of Things (IoT) and Machine …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 40–48 Read article
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Power Estimation of MAC Block for Artix 7 FPGA using Regression Technique
Abstract: This paper presents the power estimation approach using suitable machine learning technique. Artix-7 FPGA has been chosen as target FPGA (Field Programmable Gate Arrays) platform for understanding the methodology of power estimation. There are various approaches of power estimation for FPGAs have been given in the literature viz. probabilistic, statistical, and LUT based etc. However, this paper discussed a supervised machine learning approach namely curve fitting and regression analysis. The …
Published in Journal of Microcontroller Engineering and Applications · Vol. 8, Issue 3, 2021 · pp. 27–37 Read article
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
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A Machine Learning Approach for Investigating Spatial Structures between Spectral line Sources: Formaldehyde Absorptions versus Methanol Masers
Abstract: In this paper the authors present fascinating ideas on using machine learning algorithms to study connections in spatial distributions between observed spectral line sources. The method has been illustrated using observations of 4.8 GHz formaldehyde absorptions and 6.7 GHz methanol masers in the Galaxy. Both spectral line features have been well-observed in close associations with galactic star-formation regions, and we initiate this study to understand spatial connections between them. We …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 2, Issue 2, 2013 · pp. 1–11 Read article
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Identifying and Implementing a Machine Learning Model Suitable for Processing Visually Evoked Potential
Abstract: A Brain-Computer Interface (BCI) is a system that translates brain activity patterns into computer commands, bypassing physical movement. Electroencephalography (EEG) is commonly used to acquire signals in BCI research. Visual evoked potentials (VEPs) are brain responses in the visual cortex to visual stimuli. Recent studies show that exposing individuals to flickering at a consistent frequency generates EEG signals synchronized with the stimulation. Efficient extraction of VEP signals begins with preprocessing …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Survey of Techniques for Clustering and Classification of ECG using WEKA
Abstract: ECG analysis can be done for automatic detection of abnormality in cardiac activity. This can be helpful in generating alert for saving a precious life. Various techniques have been proposed in literature for feature detection and classification such as; fuzzy logic methods, artificial neural networks (ANN), and support vector machines (SVM), wavelet transform, Hilbert transform, etc. Recently, numerous researches and techniques have been developed for analyzing the ECG signal on …
Published in Journal of Microcontroller Engineering and Applications · Vol. 3, Issue 2, 2016 · pp. 14–19 Read article
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Secure Forge: Deepfake Image Detection Using Vision Transformers
Abstract: Deepfake technologies have become a major risk to the credibility and trustworthiness of digital visual information. Using powerful generative models like GANs and autoencoders, deepfakes can generate highly realistic fake videos and images, resulting in misinformation, identity theft, and public loss of trust in digital media. Classic Convolutional Neural Networks (CNNs) while being highly effective in initial-stage, deepfake detection tend to be limited by their local receptive fields and dependency …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 32–45 Read article