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398 articles for “Neural Network Techniques”
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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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Unleashing the Power of Mathematics in Natural Language Processing: Sentiment Analysis Perspectives
Abstract: Sentiment analysis (SA), which utilizes natural language processing (NLP), computational linguistics, text analysis, image processing, and video processing to extract and analyze subjective information from the internet, social media, and other sources, is becoming increasingly popular in both the business world and the scientific community. It is even possible to model it so that it focuses on polarity, sentiments and emotions, urgency, and even goals. It is able to distinguish …
Published in Recent Trends in Programming languages · Vol. 10, Issue 2, 2023 · pp. 1–9 Read article
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Support Vector Machine Inspired Load Forecasting of a State University in Haryana
Abstract: Estimating the possible environmental impact and determining probable capital requirements are made easier with a solid grasp of electricity demand. Beginning in the middle of the 20th century, demand forecasting for electric power networks was studied theoretically. Prior to that, the study of demand forecasting had not developed because of the small scale of power networks. With the use of statistical prediction techniques, plans for the electric power industry have …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 33–40 Read article
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A Review Paper on Fire Detection
Abstract: Fire is a common disastrous phenomenon that causes a serious threat to life and property. In order to protect life and property, a good fire detection system is necessary. However, the major concern with existing fire detection system design is about false alarm problem. In the present review, a fire detection system with reduced false alarm rates are identified and still the best method is suggested. Based from current literature …
Published in Journal of Industrial Safety Engineering · Vol. 1, Issue 3, 2014 · pp. 1–5 Read article
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Detection of Traffic Sign Using CNN
Abstract: For past more than half of the decade, the detection and recognition of the traffic signs are an active research area; especially in the field of automation of driving that is critical for driverless driving, as there is drastic increase in road accidents due to ignorance of traffic signs and rules. This is frequently used for recognizing permanent or temporary various road signs which are displayed on the side of …
Published in Recent Trends in Parallel Computing · Vol. 9, Issue 1, 2022 · pp. 14–23 Read article
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An Efficient Method of Fault Analysis using Artificial Neural Network
Abstract: In the power system, there are many techniques to identify and classify the faults. So, it is utmost important to choose the suitable technique. In this paper, a novel technique based on ANN have been proposed. When abnormal conditions occur in the system, the purposed method identifies and classify the fault to protect the system from the faults and stop from the big hazards. Simulation of purposed Simulink model have …
Published in Current Trends in Signal Processing · Vol. 11, Issue 4, 2021 · pp. 9–25 Read article
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An Efficient Method of Fault Analysis using Artificial Neural Network
Abstract: In the power system, there are many techniques to identify and classify the faults. So, it is utmost important to choose the suitable technique. In this paper, a novel technique based on ANN have been proposed. When abnormal conditions occur in the system, the purposed method identifies and classify the fault to protect the system from the faults and stop from the big hazards. Simulation of purposed Simulink model have …
Published in Current Trends in Signal Processing · Vol. 11, Issue 1, 2021 · pp. 9–25 Read article
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Evaluation of Credit Risk of Bank Customers with a Hybrid Approach of Data Mining Techniques
Abstract: Credit risk poses the most significant threat to financial and monetary institutions. Banks strive to offer loans that generate high returns while minimizing risk. Achieving this requires the ability to accurately identify and classify credit customers, both individuals and legal entities, according to their likelihood of fully meeting their obligations. This classification is done using relevant financial and non-financial criteria. The primary goal of this study is to assess the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 63–81 Read article
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Mode Choice Analysis: Fundamental and Models
Abstract: AbstractTravel behavior plays an important role in transportation planning. Mode choice has direct impact on the policy making decision. It is behavioral and complex in nature. The objective of this study is to carryout detailed review on various modeling methods of mode choice analysis. The factors that affect the traveler’s mode choice decision have been discussed. The methods of data collection have been briefly discussed. Further the paper highlights on …
Published in Trends in Transport Engineering and Applications · Vol. 5, Issue 1, 2018 · pp. 7–13 Read article
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An Overview and Comparative Study of Speech Recognition Techniques
Abstract: The easy way of communication between machine and human being is automatic speech recognition. Automatic speech recognition in different languages is one major research areas in signal processing field. Accuracy in SR is an important challenge in the research work. This paper discusses researches in the SR field in the past 60 years and gives an overview on SR process, types of speech, approaches, classifiers such as dynamic time warping …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 4, Issue 1, 2016 · pp. 7–12 Read article
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Skin Cancer Detection System Based on Machine Learning for Recognition of Cancerous Images
Abstract: Skin cancer ranks among the most prevalent types of cancer globally and poses significant risks when left untreated. Skin cancer arises when abnormal cells proliferate uncontrollably in the skin. This uncontrolled growth can be triggered by genetic mutations, exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds, or various other factors. In this, the early detection of cancer plays a crucial role in treatment and …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Predicting the Rice Production of Bangladesh by Machine Learning Technique
Abstract: Bangladesh is an agricultural country and its economic condition largely depends on agriculture. The country produces much agricultural merchandise like rice, jute, wheat, onion, chilly, banana, garlic, ginger, pulse and so on. However, rice (Oryza Sativa) is produced most widely all over the country. Moreover, United States Department of Agriculture (USDA), 2017 estimate that the rice production of Bangladesh is 34.7 million metric tons for the period 2017–2018 and the …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 7, Issue 3, 2018 · pp. 7–13 Read article
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AI Enhanced E-Voting System Securing Elections with Face Recognition and OTP Authentication in India
Abstract: The E-Voting domain seeks to leverage technology to address these issues, enabling citizens to vote securely and conveniently while maintaining the transparency of the electoral process. Machine learning algorithms like Haar cascade and CNN will enhance the system's security, accuracy, and efficiency by leveraging data- driven approaches. Conventional voting techniques frequently encounter obstacles including identity theft, convoluted processes, and hold-ups in the processing of results. This article suggests a complex …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 21–30 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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Harnessing NLP for Automation and Intelligence Across Sectors
Abstract: Natural Language Processing or NLP is a vital subset of Artificial Intelligence or AI which enables machines to interpret, understand, and communicate using human language in a remarkable way. From the traditional rule-based approaches to the modern advanced deep learning techniques such as transformers, neural networks, and hybrid models, NLP has been evolving year by year. This study reflects on various applications of NLP, including sentiment analysis, machine translation, analysis …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 23–32 Read article
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The Convergence of AI and Composites - A Review Anchored in Patent Trends
Abstract: The integration of artificial intelligence (AI) and machine learning (ML) techniques is revolutionizing the design, analysis, and optimization of polymer (PC/FRP), metal (MC), and ceramic matrix composites (CC). Techniques such as artificial neural networks (ANN), deep learning (DL), genetic algorithms (GA), and physics-informed machine learning (PIML) are employed to enhance property estimation, process optimization, and predictive modeling. These AI-driven frameworks enable virtual testing, application-specific material design, and real-time decision-making, while …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 182–198 Read article
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An Analysis of Machine Learning Models for Early Cardiac Risk Stratification
Abstract: The paper shows an in-depth study of machine learning and artificial intelligence solutions to early cardiac risk stratification which has a crucial necessity because cardiovascular disease (CVD) prediction remains a significant issue that needs to be improved beyond the conventional risk score. Since CVD is the most serious disease killer in the world, claiming 17.9 million deaths every year, there is a strong need to get the most sophisticated predictive …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Artificial Intelligence in Medical Fields
Abstract: Artificial intelligence (AI) is a branch of computer science capable of analyzing complex medical data. This can be used in diagnosis, treatment and predicting outcome in many clinical scenarios. Medicine and internet searches were carried out using the keywords ‘artificial intelligence’ and ‘neural networks’. An overview of different AI techniques is presented in this paper along with the review of importance in clinical applications. The proficiency of AI techniques has …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 8, Issue 1, 2019 · pp. 1–3 Read article
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Vehicle Insurance Fraud Detection Using Supervised Neural Network Model
Abstract: Vehicle insurance fraud is a serious problem that causes huge financial losses to insurance companies. In recent years, developing fraud detection models using machine-learning techniques has been of great interest. This study proposes a novel approach for vehicle insurance fraud detection using Supervised Neural network model on the Kaggle Vehicle Insurance Fraud Detection dataset. The initial step in this study involves performing data pre-processing and feature extraction on the dataset, …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 10, Issue 1, 2023 · pp. 32–39 Read article
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Evaluation and Scientific Investigation: Stock Market Forecasting Techniques
Abstract: Analysts and scholars have consistently shown interest in predicting stock market trends, a complex task given the multitude of variables influencing stock values. This article includes a thorough analysis of 50 research papers that propose methodology for stock market prediction, including Bayesian models, fuzzy classifiers, artificial neural networks (ANNs), support vector machines (SVMs) classifiers, neural networks (NNs), and machine learning techniques. The collected papers are categorized using various prediction, clustering …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 3, 2023 · pp. 26–40 Read article