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693 articles for “machine learning method”
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Unsupervised Learning Techniques in Neural Network for Face Recognition
Abstract: This paper represents the review of systematic comparison between of unsupervised learning algorithms for face recognition. In neural network, different algorithms are used for face recognition. Each algorithm has different accuracy factors. Commonly these methods asset a set of base images and serve faces as linear combo of images. In our proposed review, firstly we discuss about the face detection using neural network along with the concept of digital image …
Published in Journal of Advancements in Robotics · Vol. 7, Issue 1, 2020 · pp. 25–29 Read article
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Microstructural Design and Functional Properties of Polycrystalline Materials
Abstract: Polycrystalline materials, composed of an aggregate of crystallites or grains, are foundational to modern engineering applications due to their versatile functional properties. The microstructural design—encompassing grain size, shape, orientation, phase distribution, and grain boundary characteristics—plays a pivotal role in determining mechanical, thermal, electrical, and magnetic behavior. This abstract explores the intricate relationship between microstructure and functionality, emphasizing how tailored processing techniques such as thermomechanical treatments, sintering, and additive manufacturing can …
Published in International Journal of Crystalline Materials · Vol. 2, Issue 2, 2025 · pp. 16–20 Read article
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High-Energy Astrophysics: Exploring the Extreme Universe Through Radiation, Relativistic Phenomena, and Cosmic Cataclysms
Abstract: High-energy astrophysics is a fast-developing area of astrophysical research dedicated to exploring the universe’s most powerful and extreme events. It involves investigating dense and energetic cosmic objects and phenomena, including black holes, neutron stars, supernova remnants, gamma-ray bursts, and active galactic nuclei. These sources emit radiation predominantly in the X-ray and gamma-ray regions of the electromagnetic spectrum and are often associated with high-energy particles, including cosmic rays and neutrinos. Investigating …
Published in International Journal of Universe · Vol. 2, Issue 1, 2026 · pp. 10–15 Read article
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Machine Learning Techniques for Predicting Industries Based on Region
Abstract: In recent years, there has been a growing interest and emphasis on agricultural land preparation and its implementation among researchers, primarily due to various factors. These factors include an increased focus within the research community, a rising demand for agricultural land, and the significance of assessing soil health for ensuring robust crop production. Picture request is one such philosophy for soil and land prosperity examination. It is a staggering measure …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 1, 2023 · pp. 1–8 Read article
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Impact of Thermal Image Preprocessing Methods on a ResNet50 Model Baseline Performance for Ball Bearing Fault Diagnosis
Abstract: Ball bearings are an important part for the operational rotating machinery. To prevent it from failing, traditional engineering uses many methods. One of these is infrared thermography (IRT). IRT is a useful tool that helps monitor the situation without physical contact. But in the current world, various fields use artificial intelligence to do it more accurately & for fast detection. Deep learning models play an important role in fault detection …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 3, 2026 Read article
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Intelligent Decision Support System for Production Planning and Control in an Automotive Assembly Line
Abstract: The automobile industry has realized the importance of Intelligent Decision Support Systems (IDSS) to improve production planning and control on assembly lines. In the context of automobile manufacturing, this review paper examines the most recent developments, methodology, and applications of IDSS. Key trends, obstacles, and possibilities are discovered through an in-depth examination of the literature. Examining real-world case studies and success stories, the integration of artificial intelligence (AI) and machine …
Published in International Journal of Industrial and Product Design Engineering · Vol. 1, Issue 1, 2023 · pp. 16–21 Read article
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Innovative Approaches to Reactive Power Management and Optimization in Modern Power systems
Abstract: Reactive power management and optimization are necessary for the effective, stable, and reliable working of modern power systems. Without proper management, reactive power is responsible for additional losses in transmission, reduced capability of power transfer, and poor voltage stability conditions, thus forming a basis for developing advanced techniques of optimization. This paper discusses the innovative methods in Reactive Power Optimization (RPO) using met heuristic algorithms, namely the Self-Balanced Differential Evolution …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 44–50 Read article
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Uncovering the Elusive Threat: An Investigative Study on Polymorphic Viruses
Abstract: In the intricate landscape of cybersecurity, polymorphic viruses have prominently emerged, distinguishing themselves through their unique ability to continually modify their code, rendering them stealthy and challenging to detect. This comprehensive study embarks on a journey through the complex world of these viruses. It commences with a historical lens, meticulously tracing their roots, their initial manifestations, and the progressive sophistication of their code-altering techniques. The research then pivots to a …
Published in Journal Of Network security · Vol. 11, Issue 3, 2023 · pp. 10–21 Read article
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AI-Augmented Online Aptitude Exam System with Adaptive Testing, Intelligent Question Generation and Performance Analytics
Abstract: In the non-technological world, assessment is inflexible, catering for the diverse ability range of test takers which automatically leads to sub-optimal assessment, and sub-optimal engagement with the assessment. We have been developing an open source, AI-based exam system which will be able to meet these challenges. The Item Response Theory (IRT) and standard machine learning procedures are used. The system adjusts the difficulty level of the questions dynamically as per …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 2, 2026 · pp. 48–62 Read article
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Role of Artificial Intelligence in Quantum Materials Research
Abstract: Quantum materials have emerged as a transformative class of advanced materials due to their extraordinary electronic, magnetic, optical, and topological properties governed by quantum mechanical phenomena. These materials are expected to revolutionize next-generation technologies such as quantum computing, spintronics, superconducting electronics, nanoelectronics, intelligent sensing systems, and energy-efficient devices. However, conventional methods for discovering and optimizing quantum materials are often expensive, time-consuming, and computationally intensive because of the enormous complexity of …
Published in Journal of Materials & Metallurgical Engineering · Vol. 16, Issue 2, 2026 · pp. 13–27 Read article
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TensorFlow: Architecture, Applications, and Future Challenges
Abstract: TensorFlow, an open-source machine learning platform created by Google, has revolutionized how artificial intelligence (AI) systems are built and implemented. Designed to support scalable and flexible model training across CPUs, GPUs, and TPUs, TensorFlow enables researchers and developers to construct advanced deep learning models with efficiency and precision. This study provides an in-depth examination of TensorFlow's architecture, including its use of dataflow graphs and tensor-based computation. We explore its adaptability …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 41–50 Read article
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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article
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Electronic Resources of University Libraries: AI-Driven Management and Optimization
Abstract: In order to maximize accessibility, utilization, and efficiency, university libraries’ growing reliance on electronic resources (ER) has prompted the creation of sophisticated management techniques. The difficulty of handling enormous volumes of data has increased as educational institutions move from conventional physical collections to massive digital repositories. A key instrument in revolutionizing library operations, artificial intelligence (AI) offers creative ways to improve retrieval methods, manage digital resources more effectively, and customize …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 3, 2025 · pp. 8–15 Read article
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Image Preprocessing and Analysis on Eye Fundus Images Segmentation by Using Density Clustering Methods
Abstract: In order to do an automated evaluation of various retinal illnesses such as Diabetic retinopathy, Glaucoma, and Macular Edema, fundus images must be pre-processed first. For many reasons, it's difficult to accurately detect the optic disc. Many blood vessels cross the optic disc, making it difficult to discern the disc's boundaries in fundus images. Lesion regions in diabetic retinopathy look very much like an optic disc's colour and texture, so …
Published in Recent Trends in Sensor Research & Technology · Vol. 9, Issue 4, 2022 · pp. 11–18 Read article
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Image Preprocessing And Analysis On Eye Fundus Images Segmentation By Using Density Clustering Methods
Abstract: Abstract: In order to do an automated evaluation of various retinal illnesses such as Diabetic retinopathy, Glaucoma, and Macular Edema, fundus images must be pre-processed first. For many reasons, it's difficult to accurately detect the optic disc. Many blood vessels cross the optic disc, making it difficult to discern the disc's boundaries in fundus images. Lesion regions in diabetic retinopathy look very much like an optic disc's colour and texture, …
Published in Recent Trends in Sensor Research & Technology · Vol. 8, Issue 3, 2021 · pp. 11–18 Read article
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Transcript Summarizer of YouTube Videos Using Deep Learning
Abstract: Transcriber Sum is a deep learning-based YouTube transcript summarization tool. It employs advanced machine learning techniques to automatically generate concise summaries of YouTube video transcripts, enabling users to quickly grasp the key content and insights of videos without the need to watch or read the entire transcript. This Transcriber Sum addresses the challenge of providing users with concise and informative summaries of video content by harnessing the power of deep …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 119–126 Read article
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Advances in Analytical Chemistry Research Methodology: Trends and Applications
Abstract: Analytical chemistry is critical to scientific study because it allows for the accurate identification, measurement, and characterization of chemical compounds. Recent advances in methodology have improved accuracy, sensitivity, and efficiency, with techniques such as High-Performance Liquid Chromatography (HPLC), Gas Chromatography (GC), Mass Spectrometry (MS), and Nuclear Magnetic Resonance (NMR) spectroscopy transforming analytical procedures. The combination of Artificial Intelligence (AI) and Machine Learning (ML) has enhanced data processing, pattern recognition, and …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 12, Issue 2, 2025 · pp. 10–18 Read article
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Comparative Analysis of AI-Based Approach vs. Traditional Methods in Climate Modeling
Abstract: Climate modeling helps to predict the future of climate variations and human interference with environment. The traditional General Circulation Models (GCMs) are based on physics-derived mathematical equations but are very expensive in terms of computation. There are alternative ways to perform climate modeling in recent years with the rise and improvement of Artificial Intelligence (AI) based approaches in term of predictability, efficiency, and classification of extreme events compared to conventional. …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 26–32 Read article
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IOT and algorithmic intelligent motor health monitoring as well as maintenance prediction
Abstract: Manufacturing, transportation, and energy systems rely largely on industrial electric motors, and their untimely failure can result in expensive downtime, safety hazards, and decreased operational efficiency. The majority of traditional motor maintenance procedures rely on reactive methods or routine inspections, which frequently miss early-stage problems and lead to needless maintenance or unexpected breakdowns. This project offers an Intelligent Motor Health Monitoring and Predictive Maintenance System that combines Internet of Things …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 28–37 Read article
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Predicting Multiple Diseases Using Machine Learning: A Data-Driven Approach
Abstract: The increasing prevalence of chronic and life-threatening diseases highlights the need for innovative healthcare solutions that enable early detection and proactive management. The Multiple Disease Prediction Platform is a web-based system utilizing machine learning (ML) and deep learning (DL) algorithms to analyze user-inputted health data, generating real-time predictions of potential health risks. By leveraging Python’s Streamlit library, the platform provides an interactive and accessible diagnostic experience, eliminating the need for …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 16–35 Read article