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412 articles for “Neural Network Techniques”
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Statistical and AI Approaches to Measure Sustainability Performance of Enterprises
Abstract: Measuring sustainability performance has become a critical priority for enterprises facing increasing regulatory pressure, stakeholder expectations, and global sustainability challenges. Traditional assessment methods, largely based on static indicators and manual reporting, often struggle to capture the multidimensional, dynamic, and data-intensive nature of sustainability. This study explores the integration of statistical and artificial intelligence (AI) approaches to evaluate and enhance the sustainability performance of enterprises in a more robust, accurate, and …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 30–36 Read article
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Deep Learning Algorithms for Medical Image Encryption to Ensure Secure Data Transfer
Abstract: Deep learning has significantly impacted various fields, including medical imaging, by offering new ways to encrypt medical images for secure data transfer. This research work examines how deep learning algorithms are used to enhance medical image security during transmission. Given the high sensitivity and privacy requirements of medical data, it’s crucial to maintain its confidentiality. Traditional encryption techniques, while reliable, often struggle with issues like scalability, computational efficiency, and the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 28–36 Read article
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Breast Cancer Detection and Multiple Classification Using CNN
Abstract: Although some efforts have been made in the form of preventative screening programs, breast cancer remains one of the rising causes of death in women. Computer-assisted diagnosis is needed because of the rapidly increasing number of mammograms that can be collected by these programs. Performance metrics are not significantly improved by computer aided detection methods designed to improve diagnosis without a large number of sequential readings. In this context, self-imaging …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 12, Issue 2, 2023 · pp. 28–38 Read article
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GLAUCOMA DETECTION TECHNIQUES: A REVIEW
Abstract: The eye is the second most complex and valuable organ after the brain. The second most common among eye conditions is glaucoma, an eye disease that is widespread and has the potential to cause neurodegeneration. The main cause of Glaucoma is abnormal pressure within the eye, which can be challenging to detect in the early stages since there are no clear symptoms. A timely diagnosis plays a critical role in …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 12, Issue 2, 2024 · pp. 58–64 Read article
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Design and Optimization of Locomotive Suspension System Using Ant Colony Optimization
Abstract: The objective of design and optimization of helical spring is weight reduction with adequate strength and stiffness. Weight reduction of helical spring will contribute to the reduction of unsparing mass. This will help in improving the vibration characteristics and hence, the riding qualities of a train. Optimization is the act of obtaining the best result under given circumstances. Conventional design aims at finding an acceptable design which merely satisfies the …
Published in Trends in Machine design · Vol. 3, Issue 2, 2016 · pp. 44–49 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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AI-Assisted Gain Scheduling for Real-Time Temperature Control in Chemical Reactors
Abstract: Temperature control in continuous stirred-tank reactors (CSTR) represents a critical challenge in chemical process industries due to inherent nonlinearities, time-varying dynamics, and parametric uncertainties. Conventional proportional-integral-derivative (PID) controllers with fixed gains often fail to maintain optimal performance across varying operating conditions, leading to temperature excursions that compromise product quality and safety. This paper presents a novel AI-assisted gain scheduling framework that integrates artificial neural networks (ANN) with adaptive PID control …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 24–33 Read article
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Gait Based Person Identification Using Kohonen Self-Organizing Mapping Technique
Abstract: Though gait recognition system has some special security features, it has some limitations like viewing angle variation, slow or fast walk and carrying a bag etc. This paper has an advantage of removing these limitations by using gait energy image with Kohonen self-organizing mapping technique. This model proposes the method that is developed by Partial least square (PLS) used for features selection and singular value decomposition (SVD) used for dimensionality …
Published in Current Trends in Information Technology · Vol. 5, Issue 2, 2015 · pp. 1–6 Read article
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Advancing EEG Technology for Affordable and Effective Epilepsy Detection
Abstract: For a proper diagnosis and prompt treatment, epilepsy, a neurological condition marked by recurring seizures, needs to be continuously monitored. Manual interpretation is frequently used in traditional approaches for identifying epileptic seizures from electroencephalogram (EEG) signals, which can be laborious and error-prone. In this research, a novel method for automatically detecting epilepsy from EEG data using deep learning algorithms is presented. According to centers for disease control and prevention (CDC) …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 11–18 Read article
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A Comparative Study of Deep Learning Methods for Depression Detection in Social Media Data
Abstract: With the rise of social media platforms like Twitter, Reddit, and Facebook, individuals increasingly share personal information about their moods, behaviors, and mental states. This trend provides a unique opportunity to leverage large-scale textual data for understanding and monitoring mental health conditions, particularly depression, a prevalent and challenging mental health issue. Traditional depression assessments are often confined to clinical environments and lack the capacity for real-time monitoring. In contrast, social …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 55–65 Read article
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PREDICTING THE COMPRESSIVE STRENGTH OF CONCRETE USING ANN IN MATLAB
Abstract: This research work focuses on the production of Artificial Neural Networks ( ANNs) in the prediction of concrete compressive strength after 28 days. The measurement of the compressive strength of concrete in situ by means of cores cut from hardened concrete is recognised as the most common technique, but the compressive strength of concrete is very difficult to predict because several factors affect it.In this paper , in order to …
Published in Journal of Construction Engineering, Technology & Management · Vol. 10, Issue 3, 2020 · pp. 46–52 Read article
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Real-time Sign Language Detection Using Computer Vision and Machine Learning Techniques
Abstract: Communication plays an important role in our day-to-day lives as it assists people in sharing, and connecting to each other. Despite knowing the significance of the same, some deaf-mute pupils who are not able to communicate freely. These groups of people use sign language for sharing their thoughts. It could be a tough task to understand sign language for a group of humans who are not deaf-mute. We developed a …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 10, Issue 1, 2023 · pp. 10–19 Read article
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Deep Learning for Traffic Sign Recognition in Autonomous Vehicles: Challenges, Trends and Future Directions
Abstract: Traffic Sign Recognition (TSR) serves as a fundamental task in the domain of autonomous vehicles (AVs), enabling systems to detect, classify, and respond to road signs with the level of accuracy and speed required for safe navigation. As AV technology continues to evolve, the role of intelligent TSR systems has become increasingly vital. Traditional computer vision techniques, while foundational, often fall short under challenging real-world conditions such as poor lighting, …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 2, 2026 · pp. 1–7 Read article
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A Survey On Leveraging Machine Learning for Phishing Attack Prediction and Detection
Abstract: Phishing is one of the biggest cybersecurity threats that exploits user trust by masquerading as a legitimate site or email to steal personal and sensitive information. A state- of-the-art-phishing detection systems survey, this review showcases the evolution from traditional list-based techniques, including blacklisting and whitelisting to machine learning and deep learning models. While list-based systems cannot evolve to detect new and zero-day attacks, the ML algorithms of Decision Tree, Random …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 1–10 Read article
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Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 Read article
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AI-Assisted Kinetic Modeling of PLA Hydrolysis Under Subcritical Water Conditions for Sustainable Polymer Recycling
Abstract: The accumulation of poly (lactic acid) (PLA) in terrestrial and marine ecosystems has intensified the demand for closed-loop, green recycling technologies. Subcritical water (SCW) hydrolysis offers a promising, catalyst-free pathway for the rapid depolymerization of PLA into its constituent monomer, lactic acid. However, the complex, highly non-linear kinetics governing macro-molecular degradation under variable hydrothermal conditions limit real-time process optimization and industrial scalability. This study develops a novel artificial intelligence (AI)-assisted …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 2, 2026 · pp. 65–74 Read article
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Advanced Deep Learning Techniques for Sickle Cell Anaemia Detection
Abstract: Sickle Cell Anemia (SCA) is a prevalent genetic blood disorder characterized by the presence of abnormal hemoglobin, resulting in the distinctive sickle shape of red blood cells. Timely and accurate identification of Sickle Cell Anemia (SCA) is essential for effective management and treatment. This study presents a new method that utilizes Convolutional Neural Networks (CNNs), a deep learning model particularly effective for image analysis. The process involves using microscopic images …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 3, 2024 · pp. 9–15 Read article
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Application of Convolutional Neural Networks in Design of Efficient Pipe Flow System
Abstract: Convolutional Neural Networks exhibit remarkable capabilities in flow pattern recognition, pressure drop prediction, leak detection, and system optimization through their ability to process complex spatial and temporal data patterns. The study examines CNN architectures specifically adapted for fluid dynamics applications, including data preprocessing techniques, feature extraction methods, and performance optimization strategies. Key applications include real-time flow monitoring, predictive maintenance, design parameter optimization, and anomaly detection in pipe networks. Comparative analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 1–9 Read article
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A Novel Optimized Shunt Active Power Filter using GA and ANN in Constant Frequency Aircraft System
Abstract: Constant instantaneous power control strategy for extracting reference currents for shunt filters have been changed with the use of Artificial Neural Network and Genetic Algorithm primarily based controller and their performances were compared. The acute evaluation of comparison of the repayment capability mostly based on THD and velocity could be carried out, and guidelines might be given for the selection of the technique for use. The simulated effects the use …
Published in Journal of Aerospace Engineering & Technology · Vol. 8, Issue 1, 2018 · pp. 36–43 Read article