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147 articles for “Neural networks”
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Feature Extraction: Comparing Feature Extractors
Abstract: Machine learning is getting fuzz nowadays a lot. In order to train the computer to recognize the set of images is the key factor. For this neural networks and classifiers are used to do the identification and recognition. Now do the matching feature points or the interest points are required which makes it to our area of research i.e. feature extractors. In our paper we compared various feature extractors Fast, …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 4, Issue 1, 2018 · pp. 12–17 Read article
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Deep Learning in Medical Image Classification and Object Detection: A Survey
Abstract: Deep learning methods have demonstrated superior performance in the area of computer vision, speech recognition, natural language processing, healthcare, and many more. Convolutional neural networks (CNNs) are a class of deep learning methods that have the ability to learn from raw data available as images, audio, or text. CNNs have become a powerful tool for variety of pattern recognition tasks due to the availability of abundant data and GPU-based training. …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 8, Issue 2, 2022 · pp. 1–15 Read article
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Facial Expression Recognition by Using Multifeatured Fusion And Deep Learning Techniques
Abstract: In our daily lives, sentiment analysis is a vital part of communication. A vital component is information regarding how the user feels when someone communicates. You will need a solution that can handle everything from recognizing a user's emotional state to personalizing the user experience. This study's objective is to look into emotions. Today, deep learning techniques are quickly advancing in a variety of fields, including computer vision. Without a …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 8, Issue 2, 2022 · pp. 16–22 Read article
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Criminal Face Identification Using Deep Learning and Machine Learning
Abstract: Criminal face identification is a crucial task for law enforcement agencies to prevent and solve crimes. The traditional methods for identifying criminals using human expertise and eyewitness testimonies have several limitations, such as subjectivity, inaccuracy, and unreliability. Machine learning and deep learning techniques have yielded promising gains in facial recognition and identification applications in recent years. In this study, we propose a criminal face identification system that combines machine learning …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 9, Issue 1, 2023 · pp. 28–34 Read article
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A Review of Modeling and Data Mining Techniques Applied for Analyzing Steel Bridges
Abstract: The vibration response data measured from the structure contains uncertainties and requires different techniques for its analysis. The present study involves the comprehensive review of the model based and data mining techniques which are frequently applied by various researchers in past to solve various multi criteria decision making and analysis problems. The selection of suitable technique for specific problem is required to obtain accurate outcomes. The literature survey is done …
Published in International Journal of Software Computing and Testing · Vol. 7, Issue 1, 2021 · pp. 1–15 Read article
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Trends and Techniques of Software Cost and Performance Measurement
Abstract: Software measurement is an evolving aspect of software engineering providing the necessary support to plan, execute, control, and improve the software development process. However, Software metrics constitute a set of acceptable variables of measurement encompassing diverse activities that require some level of quantification of which cost, and effort estimation are inclusive. This study was aimed at reviewing the various trends and techniques in software cost and performance measurement. The study …
Published in International Journal of Software Computing and Testing · Vol. 8, Issue 1, 2022 · pp. 6–12 Read article
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Unlocking the Potential: Machine Learning Driven Explainable AI Applications Across Diverse Domains
Abstract: Explainable artificial intelligence (XAI) aims to make discoveries and output generated by machine learning algorithms accessible to human users in a trustworthy and easy-to-understand manner. It describes the impact of an AI model and any potential biases, helping in characterizing models with accuracy, fairness, transparency, and outcomes in decision-making powered by AI. XAI focuses on understanding the data used to train the model, its predictions, the specific elements involved in …
Published in International Journal of Software Computing and Testing · Vol. 9, Issue 1, 2023 · pp. 24–32 Read article
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The Foundations and Principles of Computational Intelligence
Abstract: Artificial intelligence (AI) assumes a driving part in security administrations. A dynamic model Intelligent Intrusion Detection System (IIDS), in view of particular AI approach for intrusion detection. The strategies that are being explored incorporate neural networks and fuzzy logic with network profiling that uses basic data mining procedures to handle the network data. Suspicious interruptions can be followed back to its unique source way and any traffic from that specific …
Published in International Journal of Analog Integrated Circuits · Vol. 1, Issue 2, 2015 · pp. 17–33 Read article
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Real Time Face Mask Detection with Deep Learning
Abstract: The pandemic because of COVID-19 needs no introduction. An all-too-important and successful weapon against it has been the utilization of face masks. A special technique is presented in this paper for detecting automatically whether someone is wearing a mask or not, contingent on the machine learning technique. The findings can be utilized by authorities to warn or fine people for not wearing mask, especially at public places. This work relies …
Published in International Journal of Analog Integrated Circuits · Vol. 7, Issue 1, 2021 · pp. 8–14 Read article
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A Comparative Study Of RCNN, YOLO V3-Tiny and YOLO V5 Object Classification Architectures for Accurate Object Classification in Military Domain
Abstract: Late advances in object distinguishing proof computations consolidate speedy and faster RCNN whichmade the ID times also low with high accuracy. In this paper, we demonstrate the reliability of asuggested computation that employs RPN (Region Suggestion Associations) and Fast RCNN (RegionbasedConvolutional Neural Networks) for the distinguishing proof. The RPN gives region suggestionsfrom that we give the ROI (Regions of Interest) as commitment to the RCNN association, it will ingeneral be …
Published in International Journal of Broadband Cellular Communication · Vol. 7, Issue 1, 2021 · pp. 19–37 Read article
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Dynamic system identification for looper tension control Using BPNN & Kalman Filtering
Abstract: System identification is an important area in control system. This paper discuss some of the reasons that causes the slow convergence of Back Propagation Neural Network (BPNN). This paper also comment on the effect of the number of neurons in the hidden layer when apply BPNN with Kalman Filtering to dynamic system identification for a looper tension control. BPNN is based on LMS, and uses steepest descent method to find …
Published in International Journal of Electrical Power System and Technology · Vol. 1, Issue 1, 2015 · pp. 38–43 Read article
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Prediction of Adsorption Energies using Machine Learning
Abstract: In this article, we have a much more comprehensive method that promotes the exploration of automated descriptors. Primary component analysis (PCA) with varimax rotation is used to find the strongest minimum range of adsorption energies that can be used as metal descriptors for a given data set. Our findings demonstrate that the mixture of descriptors produced by this method outperforms conventional descriptors such as nuclear carbon, hydrogen and oxygen adsorption …
Published in International Journal of Electrical Power System and Technology · Vol. 6, Issue 2, 2020 · pp. 38–46 Read article
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Evaluation of Two Distinct AI Control Methods to Enhance Power Quality
Abstract: Artificial Intelligence techniques are the latest techniques utilized for the improvement of electrical performance. This study examines and contrasts various artificial harmonic reduction methods for source current. Artificial Intelligence may include Fuzzy logic and Artificial Neural Network. The goal of the modeling is to improve the power quality through the application of principles that cannot be expressed as "true" or "false" but rather as "partially true" called as Fuzzy logic …
Published in International Journal of Electrical Power System and Technology · Vol. 8, Issue 2, 2022 · pp. 15–26 Read article
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Internet of Thing
Abstract: We are entering a new era of the computing technology that many are calling the Internet of Things (IoT). Machine to machine, machine to infrastructure, machine to environment, the Internet of Everything, the Internet of Intelligent Things, intelligent systems call it what you want, but it is happening, and its potential is huge. We see IoT as billions of smart, connected “things” (a sort of “universal global neural network” in …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 3, Issue 1, 2017 · pp. 5–8 Read article
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Privacy Policy Summarization and Detection of Unfair Clauses
Abstract: ABSTRACTLess than 1% of all users read the privacy policies (or terms and conditions) that accompany software products. This can be attributed to their low level of readability, length, and complexity. Hence, this allows corporations to sneak in clauses which may compromise a user’s privacy, allowing them to use their data for monetary benefit. For example, corporations may sell user data to third parties for targeted advertising. To tackle this, …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 6, Issue 1, 2020 · pp. 35–41 Read article
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Multi-Modal Summarization for Digital Data
Abstract: ABSTRACTText summarization aims to abbreviate input text into a compact form. Automatic data summarization is one of the field of data mining. The increase in expansion of data communication over the net makes it crucial to create Multi-Modal Summarization (MMS) from synchronous data (text, audio, image and video). The MMS method combining the techniques of Natural Language Processing (NLP), speech processing, computer vision, and Advanced Encryption Standard (AES) encryption used …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 6, Issue 1, 2020 · pp. 28–34 Read article
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A Research Paper on Self Driving Car
Abstract: A summary of the main idea of this subject is to extend the autonomous community of the vehicle, they will explore their environment, and are able to move without human intervention. This article suggests that vehicle automation, with the help of the placement of road signs, traffic signs, barriers, warning, response, and decision, including the fact that changing the direction of the car, to prevent the raspberry screen, the prevention …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 7, Issue 1, 2021 · pp. 1–6 Read article
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Knowing Captchas Using Deep Learning
Abstract: Websites can use CAPTCHA (Completely Automated Public Turing Test to Differentiate Computers from Humans) to distinguish between humans and machines and prevent automated attacks by programmers and malicious programmers. Studies on CAPTCHA recognition have the potential to uncover security flaws, advance CAPTCHA technology, and even advance handwriting and license plate recognition. However, the whole objective of the CAPTCHAs can be bypassed by utilizing the principles of deep learning and computer …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 8, Issue 2, 2022 · pp. 30–40 Read article
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Analyzing Crowds with Deep Learning: A Review of Methods and Challenges
Abstract: With the growing population, the need for an effective crowd management tool emerged. It is important to monitor and analyze unusual crowd movements and behavior for many applications such as peaceful events, protests, gatherings, or traffic management. Current systems, such as video surveillance, are a useful technique for crowd monitoring, but they require human visual capabilities to monitor the crowd. This work is a paper on Crowd Analysis using convolution …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 9, Issue 2, 2023 · pp. 30–42 Read article
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OODA Principles for Finding Unknown Malware
Abstract: This paper is planned to give a model to "OODA Principles for Finding Unknown Malware", it portrays the state's general necessities with respect to the securing and execution of intrusion prevention and detection systems with intelligence (IIPS/IIDS). This is intended to give a more profound comprehension of interruption aversion and recognition standards with knowledge may be in charge of getting, actualizing or checking such frameworks in comprehension the innovation and …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 1, Issue 2, 2015 · pp. 1–12 Read article