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398 articles for “Neural Network Techniques”
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Bearing Defect Diagnosis: An Approach for Manufacturing Industries Using Wavelet Transform Based Features
Abstract: To maintain reliability in the manufacturing units, industries have concentrated their attention on the condition based maintenance. Fault detection and diagnosis are the two of three condition based maintenance mainstays. Bearing is one of the most important and essential components of the rotating machines. Hence, the researchers have shown their interest in bearing fault detection and diagnosis from the last few years. They mainly use bearing vibration as fault characteristics …
Published in Journal of Microelectronics and Solid State Devices · Vol. 4, Issue 1, 2017 · pp. 15–21 Read article
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Brief Review of Medical Image Fusion Techniques Based on Hybrid Intelligence
Abstract: An image fusion combines complementary images from multiple images such that the fused image is more suitable for further processing tasks or specific application. The goal of image fusion is to integrate complementary multi sensor, multi temporal and/or multi view data into a new image containing more information for proper medical diagnosis and different application tasks. The purpose of this paper is a survey of image fusion algorithms based on …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 3, Issue 1, 2016 · pp. 8–15 Read article
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Survey on Techniques to Segment Salt Bodies in Seismic Images
Abstract: The areas in the earth which are rich in oil and natural gas also have huge deposit of salt below the surface. So, it is very important for the hydrocarbon industries to acquire the needed resources. The important challenge of seismic imaging is to detect subsurface salt structure which is required for the identification of hydrocarbon reservoirs and drill path planning. Unfortunately, the accurate identification and classification of large salt …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 8, Issue 1, 2021 · pp. 25–30 Read article
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Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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YOLOv8 in Focus: A Review of its Application in Driver Monitoring Systems
Abstract: This research presents a novel Driver Monitoring System (DMS) that utilises Convolutional Neural Networks (CNNs) to achieve remarkable results. Specifically, the YOLOv8 (You Only Look Once version 8) detection technique is used. The main goal is to increase road safety by using cutting-edge computer vision techniques to analyse driver behaviour in real-time. The YOLOv8 detection method, a cutting-edge CNN model renowned for its precision and effectiveness in object recognition, is …
Published in Journal of Electronic Design Technology · Vol. 14, Issue 3, 2023 · pp. 35–40 Read article
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An Automation Detection for Sign Language Using AI
Abstract: Sign language recognition has attracted considerable interest because of its ability to facilitate communication between the deaf community and the public, thereby bridging communication divides. Traditional approaches to sign language recognition often face challenges in accurately interpreting the complex and nuanced gestures inherent in sign languages. However, recent advancements in deep learning techniques have shown promising results in improving the accuracy and robustness of sign language recognition systems. This study …
Published in Recent Trends in Programming languages · Vol. 11, Issue 1, 2024 · pp. 1–14 Read article
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Artificial Neural Networks for Brain Controlled Artificial Legs and Brain Computer Interface (BCI)
Abstract: AbstractThe whole system is guarded with the support of highly developed microcontrollers and digital signal processors. The signals square measure taken out from the human brain with the assistance of electroencephalography technique. The person will perform operations like walking, running etc. simply by their thought. These methods are going to be significantly appropriate for people who lose their legs in accidents and the planned system is hundred percentages possible within …
Published in Journal of Advancements in Robotics · Vol. 4, Issue 2, 2017 · pp. 1–4 Read article
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Alzheimer's Diseases Risk Level Classifications Using Chaos Technique
Abstract: This paper aim to classify Alzheimer's diseases risk level determining Dementia and Epilepsy which is a collective term used to describe the problems that people with various underlying brain disorders or damage can have with their memory, language and thinking. Alzheimer disease is the best known and most common disorder under the umbrella of Dementia and Epilepsy. Brain functions are measured in the hope of determining and differentiating certain functional …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 2, Issue 2, 2015 · pp. 36–46 Read article
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A Detailed Survey on Crime Detecting and Clustering Technique in Data Mining
Abstract: AbstractData mining is the extraction of useful information or the knowledge from the set of data or it’s the process analyzing the data from the various perspectives and summarizing into information which is useful. Detection of crime begins with discovery of crime scene, and proceeds from side to side the process of evidence collected works, identification and the analysis. It is called as an act that is being committed or …
Published in Journal of Advanced Database Management & Systems · Vol. 4, Issue 2, 2017 · pp. 19–26 Read article
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Malicious Network Traffic Detection Using Hybrid Feature Selection with Ensemble Neural Network
Abstract: The detection of malicious network traffic is a critical aspect of cybersecurity, aiming to protect sensitive data and maintain the integrity of network systems. This study introduces a novel approach that combines hybrid feature selection with ensemble neural networks to enhance the accuracy and efficiency of malicious network traffic detection. The dataset used in this study was obtained from Kaggle and offers a wide-ranging and varied collection of network traffic …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 3, 2025 Read article
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Comparison of Simulations Results of Fuzzy Logic, Neural Network and Conventional Scheme Based Controller for SAF in Constant Frequency Aircraft System
Abstract: SRF control strategy for finding reference currents for active power filters have been optimized using artificial neural network, fuzzy logic control and their performances have been evaluated. The acute analysis of comparison of the compensation capability based on THD and speedwell be done, and recommendations will be given for the choice of technique to be used. The simulated results using MATLAB model are shown, and they will undoubtedly prove the …
Published in Journal of Aerospace Engineering & Technology · Vol. 7, Issue 1, 2017 · pp. 1–9 Read article
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Animal Species Prediction Using Deep Learning
Abstract: In the face of escalating biodiversity loss, effective monitoring of animal species is critical for conservation efforts. This study presents a deep learning approach for species detection and a multimodal feature identification technique for animals vulnerable to poaching. The suggested prediction system recognizes objects automatically by the application of deep learning techniques to detect objects and then recognize them by using computer vision techniques, and it is triggered when an …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 14–22 Read article
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Bearing Fault Diagnosis Using ANN and SVM with the Help of Wavelet Transform Based Features
Abstract: Many researchers use vibration signals as fault characteristics of any rotating bearing for fault detection and use various optimization techniques available for fault of bearing classification. The method of fault classification uses few neural network (NN) geometry and parameters necessary for the formulation. There is no derived formulation which can be used to select the optimal values for the network parameters. The parameters which are required to be calculated, impacts …
Published in Recent Trends in Electronics Communication Systems · Vol. 4, Issue 2, 2017 · pp. 26–34 Read article
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Faults Detection Techniques of Three Phase Induction Motor: A Review
Abstract: Induction motors are the most commonly used machines in industries. It is very robust, inexpensive and easy to maintain. Induction motors appear to various faults during their operation. Accurate fault identification is the prime industrial need to reduce breakdown, maintenance and revenue losses. Therefore, an early fault detection is needed for the protection of the motor against electrical and mechanical failures for continuing their operation safely. The main perspective of …
Published in Journal of Control & Instrumentation · Vol. 9, Issue 1, 2018 · pp. 45–49 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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An Overview of Artificial Neural Network and its Applications
Abstract: This paper presents an overview of Artificial Neural Network (ANN). The study of neurons and its discrete representation by the set theory is the key objective of this paper. New data structure technique is proposed in this paper by using the mechanism of (ANN). The finite dimension of the field is generalized in this paper. The linear transformation and the representation of the vector basis are applied to propose the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 2, 2020 · pp. 17–20 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 Split and Merge UNet: A Deep Learning Assisted UNet Model to Segment Corpus Callosum of Brain for Automatic Autism Detection
Abstract: In recent years, deep learning techniques have shown remarkable performance in various image analysis applications, particularly in the domain of medical image processing. Among these, image segmentation plays a critical role, as it helps in isolating and analyzing specific regions within medical images. The proposed study focuses on segmenting the corpus callosum, a vital structure in the human brain, using a novel optimization technique known as the Split and Merge …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Review of Deep Learning in Medical Imaging
Abstract: In the past few years, computer-aided analysis has fallen quickly behind. Organ categorization and segmentation is a key stage in computer-aided diagnosis. In recent years, there has been a lot of interest in the division of abdominal organs such as the liver, stomach, kidney, pancreas, and bladder from various picture modalities. Radiologists or medical specialists analyze abdominal pictures the majority of the time. Due to subjectivity, intricacy of the picture, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 9, Issue 3, 2022 · pp. 16–24 Read article
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Comparison and Analysis of Facial Emotion Detection Using Various Deep Learning Neural Networks
Abstract: Facial emotion recognition employs Convolutional Neural Networks (CNNs), Residual Networks (ResNet), Long Short-Term Memory (LSTM) networks, and Deep Neural Networks (DNNs) to automatically identify various emotions, including disgust, anger, fear, happiness, sadness, surprise, and neutrality. This study utilizes transfer learning along with data preprocessing techniques such as rotation, flipping, brightness adjustment, and enhancement methods. Traditional machine learning models achieve an accuracy range of 45 to 50%. In contrast, our proposed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 37–42 Read article