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579 articles for “Learning Techniques”
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Comparison of K-nearest Neighbor and Artificial Neural Network Classifiers for the Detection of Breast Cancer
Abstract: Breast cancer is the most common type of cancer seen in women in the present day, which is also considered a life-threatening disease. If this cancer can be detected in its early stage it can be a lifesaver for many people around the world. Machine Learning techniques have become one of the hotspots for predicting the early diagnosis of breast cancer. This research work experiments with the two most popularly …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 78–83 Read article
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Generic Virtual Mouse
Abstract: The mouse and keyboard have been replaced by new input mechanisms brought about by the quick development of Human-Computer Interaction (HCI). Using computer vision and deep learning techniques, this study explores the possibility of replacing actual mouse inputs in a computer system with hand gestures. We created a virtual mouse system that uses a normal webcam to record hand motions. Computer vision algorithms then process these gestures to handle mouse …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 26–32 Read article
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Detection of Pneumonia in COVID-19 Patients Using X-ray Images
Abstract: This study explores the use of chest X-ray image analysis and deep learning methods to identify pneumonia in COVID-19 patients. Due to the pandemic, Proper as well as immediate examination of COVID-19 is now essential for patient care and disease control. This study proposes a novel approach that uses convolutional neural networks (CNNs) to automatically predict pneumonia in COVID-19 patients using chest X-ray images. In this study, an X-ray of …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 13–23 Read article
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Illuminating the Frontier of Drug Discovery: Unleashing the Power of Bioinformatics for Unprecedented Breakthroughs
Abstract: It takes a long time and a lot of effort to discover and develop new drugs, which necessitates extensive study and testing. With the help of computational techniques and data analysis, bioinformatics has grown to be a potent tool for drug discovery in recent years, allowing researchers to find new drugs faster. In this review, we examine the role of bioinformatics in drug discovery, including the use of ligand- and …
Published in International Journal of Molecular Biotechnological Research · Vol. 1, Issue 2, 2023 · pp. 1–10 Read article
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Attendance System Based on Facial Recognition
Abstract: Attendance management is a fundamental aspect of educational institutions and workplaces, ensuring accountability, discipline, and operational efficiency. Traditional methods, such as manual roll calls, RFID cards, and fingerprint scanners, are often time-consuming, error-prone, and susceptible to fraud. This research presents an automated attendance management system utilizing face recognition technology to address these challenges effectively. The proposed system employs OpenCV for real-time image processing, the face recognition library for accurate facial …
Published in International Journal of Electronics Automation · Vol. 3, Issue 1, 2025 · pp. 28–34 Read article
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Enhance Thermal and Conductive Properties through Graph Neural Network-Based Machine Learning-Driven Advanced Polymer Material Design
Abstract: Advanced polymer materials are widely used in modern engineering and manufacturing because of their lightweight nature, flexibility, durability, and adaptability to different applications. However, designing polymer materials with enhanced thermal and electrical properties remains a challenging task. The performance of polymers is influenced by a complex combination of molecular structures, filler materials, processing parameters, and nanoscale interactions. Conventional optimization methods often require extensive experimental trials and computational resources, making it …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Federated Learning for Energy Management in Next Generation Smart Cities
Abstract: Federated learning has emerged as a promising approach for addressing the challenges of energy management in next-generation smart cities. This decentralized approach to machine learning allows collaborative model training among distributed data sources, while safeguarding data privacy and security. In this study, we explore the application of federated learning techniques to optimize energy consumption, enhance grid stability, and promote sustainability in smart city environments. By aggregating data from diverse sources …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 1, 2024 · pp. 19–27 Read article
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A Study on the Role of Artificial Intelligence in Indian Higher Education System
Abstract: In the present era, Artificial Intelligence (AI) has been transforming learning, teaching, and engaging, by making them more personalized and efficient in every field. In Indian Higher Education system, the application of Artificial Intelligence (AI) technology is improving learning techniques, by natural language processing, machine leaning etc. by students for analyzing data, using algorithms, discovering patterns and making the predictions for outcomes; and instructors may make lessons for each student …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 08–12 Read article
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Depression Detection using Machine Learning: A Comprehensive Review
Abstract: Depression is a leading mental health disorder worldwide, often underdiagnosed due to subjective assessment methods. The increasing availability of digital behavioral data and the advancement in machine learning (ML) have opened new avenues for automated depression detection. This review presents a comprehensive overview of recent developments in ML- based approaches for detecting depression. It explores data sources, feature extraction techniques, learning algorithms, evaluation methods, and highlights current challenges and future …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 Read article
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Robust Classification of Traffic Signs Using Relief Feature Reduction Technique
Abstract: Ensuring driver safety amidst the rapid growth of global population and vehicular density continues to be a paramount challenge for transportation authorities and governments worldwide. With the rise of smart mobility solutions and autonomous driving technologies, the ability to detect, classify, and respond to traffic signs accurately has become critically important, especially under diverse and adverse environmental conditions such as rain, fog, or poor lighting. Reliable traffic sign recognition not …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 30–37 Read article
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Recent Trends in Fluid Mechanics with Emphasis on Aeroacoustics and Flow-Induced Noise Control
Abstract: Fluid mechanics continues to evolve rapidly due to increasing demands in aerospace, automotive, energy, and environmental engineering applications. Recent trends in this field highlight significant advancements in both theoretical understanding and practical implementations, particularly in complex flow phenomena. Among these, aeroacoustics and flow-induced noise control have emerged as critical research areas due to their direct impact on system performance, efficiency, and environmental sustainability. Aeroacoustics deals with the generation, propagation, and …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 1, 2026 · pp. 32–38 Read article
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Alzheimer’s Disease Detection Using ML Algorithm
Abstract: A degenerative neurological state of affairs, Alzheimer's disease (AD) gradually impairs cognitive and functional capacities, especially in people over 65. Early AD detection is crucial for efficient management and treatment prep. This study delves into novel approaches for the early detection of AD using non-invasive methods. We've implemented a blend of neuroimaging data analysis and machine learning algorithms to pinpoint markers indicative of the disease during its initial phases. Our …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 3, 2024 · pp. 53–57 Read article
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Bias Detection and Accuracy Enhancement in Voice-based Banking Authentication Using Deep Learning
Abstract: Biometric systems have become an integral part of how many people access banking services today, and voice verification systems can be a secure and easy-to-use source of banking authentication that does not require any physical contact with the bank or any other person. From the security perspective, these systems would normally provide an effective means of identifying an individual but frequently exhibit bias with respect to demographics such as the …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
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An Approach Towards Chatbot Using Speech Recognition
Abstract: Chatbot is software that, rather than facilitating direct interaction with a live human agent, conducts online conversations using text or text-to-speech. It is designed to accurately mimic human behavior during conversation. This paper presents a proposed chat system that dynamically responds to web-based customer queries. Speech recognition is the basis of the artificial intelligence used in the proposed system. The web-based platform provides a large intelligence base to help simulate …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 1, 2024 · pp. 1–5 Read article
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A Comparative Study Between GSM and CNN to Develop Gesture Detection Based Alert System for Women Safety
Abstract: Women’s safety is a pressing issue in today’s world, and technology can play a crucial role in addressing it. This project introduces a facial expression recognition device that uses Convolution Neural Network (CNN) technology and develop it’s comparison with an expression system with use of GSM is done. Unlike traditional methods relying on manual activation or dedicated devices, this system reacts instantly to threatening situations by recognizing predefined gestures, ensuring …
Published in International Journal of Electrical Power and Machine Systems · Vol. 2, Issue 1, 2024 · pp. 24–30 Read article
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Adaptive Drift Correction in Polymer-Based Wearable Biosensors via Data-Driven Signal Modeling
Abstract: Polymer-based wearable biosensors have emerged as a promising technology for continuous health monitoring due to their mechanical flexibility, biocompatibility, and suitability for long-term physiological interfacing. However, prolonged exposure to biofluids, environmental variability, and mechanical deformation introduces signal drift, which significantly degrades measurement accuracy and limits clinical reliability. This paper presents a data-driven methodology for compensating signal drift in polymer-based wearable biosensors using adaptive signal processing and machine learning techniques. The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 131–139 Read article
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Fruit Adulteration Detection Utilizing Machine Learning Methods
Abstract: A device utilizing Internet of Things (IoT) technology was developed for the identification of fruit adulteration through machine learning methods, specifically targeting formalin content assessment. The identification of the fruits based on their extracted traits has been accomplished using a variety of machine-learning techniques. The formalin concentration can be detected as an estimate of the generated voltage of any fruit via an Arduino Uno board 3 and a volatile compound …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 1, 2023 · pp. 32–45 Read article
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AGRISMART: Crop and Soil Management System
Abstract: Agriculture has played a crucial role in developing countries where the majority of the rural population relies on it for their livelihoods. A finer-grade crop classification has become crucial in the context of precision agriculture. In recent years, the volume of open image data has grown significantly. This can be used in combination with machine learning techniques to classify crop types in the agricultural industry. The proposed crop species recognition …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 · pp. 50–55 Read article
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A Study of Cloud-Enabled Deep Learning for Monitoring and Predicting Soil Health in Agriculture
Abstract: Soil health is a critical factor in ensuring sustainable agricultural practices and food security. Traditional methods for soil health assessment are often time-consuming, localized, and lack scalability. This study explores the integration of cloud-enabled deep learning techniques to monitor and predict soil health efficiently. Leveraging data from IoT sensors, satellite imagery, and lab-based analyses, a cloud-based framework is proposed to process and analyze soil health parameters such as pH, moisture …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 8–16 Read article
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A Threshold-Weighted Mathematical Fusion Model for Epidemic Outbreak Prediction Using SEIR Residual Dynamics and Cloud-Based Machine Learning
Abstract: Accurate prediction of epidemic outbreaks is critical for effective public health management, resource planning, early warning generation, and timely intervention by municipal authorities. Traditional compartmental models such as Susceptible–Exposed–Infectious–Recovered (SEIR) offer valuable epidemiological insights and mathematical interpretability; however, they may not adequately capture the complex nonlinear relationships present in real-world urban health systems. Conversely, data-driven machine learning techniques can identify hidden patterns in large datasets but often lack epidemiological structure …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 12–19 Read article