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147 articles for “Neural networks”
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Design A Kaiser Window Based Digital Filter by Using GRNN
Abstract: In this paper, we have designed the digital filter based on Kaiser Window function using ANN. Firstly we have designed the 10th order digital filter based on Kaiser Window function then calculate the coefficient of designed filter. Similarly this process is repeated for the 15th and 20th order. We have normalized the frequency and designed filter at frequency ranges 0.05 to 0.95 Hz. Then we calculated the coefficients of filter …
Published in International Journal of Microwave Engineering and Technology · Vol. 2, Issue 1, 2016 · pp. 39–44 Read article
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Anomaly Detection Network for Surveillance Video
Abstract: Anomaly Activity is the prediction of a suspicious activity from a picture or video. This project would include using neural networks to detect suspicious human activity from real-time CCTV video. Human Anomaly Activity is a central issue in computer vision that has been researched for over 15 years. It is significant due to the large number of applications that can benefit from Activity detection. Human pose estimation, for example, is …
Published in International Journal of Software Computing and Testing · Vol. 7, Issue 2, 2021 · pp. 13–20 Read article
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Machine Learning-Based Channel Estimation for 5G NR Systems: A Comprehensive Review of TDL/CDL Channel Models and CNN Architectures
Abstract: Accurate channel estimation is a fundamental requirement for reliable communications in fifth-generation New Radio (5G NR) systems, where highly dynamic propagation environments impose severe challenges on conventional pilot-based methods. This study provides a thorough analysis of channel estimate methods for 5G NR, including everything from contemporary deep learning (DL) techniques based on Convolutional Neural Networks (CNNs) to traditional Least Squares (LS) and Minimum Mean Square Error (MMSE) estimators. Our analysis …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 2, 2026 Read article
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On the Performance of Adaptive Intelligent Wireless Senor Nodes Nanostructured Array for IoT Applications
Abstract: Nowadays practically everyone has a mobile device, and those numbers are getting higher, parallel, the number of interactive multimedia applications is also increasing, and this trend will continue in the future. Wireless sensor node data can be used for a variety of applications, including environmental monitoring, industrial automation, and smart home systems. In other circumstances, the nodes may be able to process and analyze the data locally before communicating it …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 9, Issue 2, 2023 · pp. 29–39 Read article
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A Review of AI and Machine Learning Techniques in Dew Point Pressure Prediction for Gas Condensate Systems
Abstract: Condensate gas reservoirs pose considerable management challenges due to their intricate phase behavior and the critical need for accurate predictions of dew point pressure (PDew). A precise determination of PDew is vital for optimizing production strategies, estimating reserves, and planning enhanced oil recovery operations. Traditional methods for PDew determination often involve experimental analyses that can be both costly and time-consuming, highlighting the necessity for alternative predictive models. This review consolidates …
Published in International Journal of Chemical Engineering and Processing · Vol. 11, Issue 1, 2025 Read article
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An Integrated Machine Learning and IoT-Based Framework for Predictive Urban Water Demand Management and Distribution Optimization
Abstract: Abstract Urban water resource management has become increasingly complex due to rapid urbanization, population growth, climate variability, and aging infrastructure. Conventional water management approaches are often reactive, inefficient, and incapable of handling real-time fluctuations in demand and supply. This study proposes an integrated framework that combines machine learning (ML) techniques with Internet of Things (IoT)-based real-time monitoring to enhance water demand prediction and optimize distribution systems in urban environments. The …
Published in International Journal of Water Resources Engineering · Vol. 12, Issue 1, 2026 Read article
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ANN Based Power Quality Identification and Classification in Wind Solar Hybrid System
Abstract: With the development of new functionalities solar and wind energy based hybrid system are upcoming energy source with higher efficiency. Solar and wind energy being naturally available in abundance and non-polluting is one of the most promising sources. Due to the development of modern power electronics devices the power quality of wind solar hybrid system gets affected. Hence due to the increasing usage of sensitive electronic equipments in wind solar …
Published in International Journal of Electrical Power System and Technology · Vol. 3, Issue 2, 2017 · pp. 6–11 Read article
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AI-Integrated Precision Agriculture System for Fertilizer Optimization, Multimodal Crop Yield Prediction
Abstract: Agriculture is rapidly transforming into a data-driven ecosystem supported by advances in artificial intelligence (AI), Internet of Things (IoT) sensor networks, and satellite remote sensing technologies. These innovations enable precision-driven decision-making aimed at improving productivity while minimizing environmental impact. This paper presents an AI-integrated precision agriculture system designed to optimize fertilizer usage and enhance crop yield prediction accuracy through a robust multimodal deep learning framework. The proposed approach integrates heterogeneous …
Published in International Journal of Plant Biotechnology · Vol. 12, Issue 1, 2026 · pp. 11–17 Read article
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AI-Based Image Detection of Rice Crop Diseases Using Deep Learning and Grad-CAM
Abstract: The Indian economy relies heavily on agriculture, and rice is one of the most significant staple crops grown in the country. Nevertheless, rice cultivation faces numerous challenges due to several leaf diseases, such as bacterial leaf blight, brown spot, and leaf smut. These diseases can lead to substantial yield losses and financial burdens for farmers. Therefore, the early detection and classification of these diseases are essential to minimize crop damage …
Published in International Journal of Plant Biotechnology · Vol. 12, Issue 2, 2026 Read article
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Health Care System Analysis Using Different Datasets
Abstract: In this research work, we have discussed data science and various machine learning algorithms like KNN, Support Vector Machine, Artificial neural network, Random forest etc. and the results obtained from these algorithms which can be used for the prediction of heart disease, cancer and in many other fields of medical science. Requirement of data cleaning along with various methods of data cleaning are mentioned here, along with these various issues …
Published in International Journal of Distributed Computing and Technology · Vol. 8, Issue 2, 2022 · pp. 29–37 Read article
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Comparison Analysis of Lumpy Skin Disease Detection System Using X-Ray Images of Animals with the Help of Deep Learning
Abstract: Lumpy Skin Disease (LSD), caused by the Capripoxvirus, is a highly contagious viral infection impacting cattle and other livestock, resulting in significant economic losses due to decreased productivity and mortality. Early detection is critical to mitigate its spread and reduce its impact on agriculture and dairy sectors. This study investigates the efficacy of deep learning methodologies for detecting LSD through X-ray images, offering a non-invasive diagnostic approach to identify internal …
Published in International Journal of Animal Biotechnology and Applications · Vol. 11, Issue 2, 2025 · pp. 1–5 Read article
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Adaptive Text_Summarization: A Meaningful Summarization of Reviews
Abstract: Adaptive text_summarization is a model which takes elaborated data set of reviews containing more than two attributes as input and further breaks down those large chunks of text into summarized - form by eliminating attributes which are of less important for final evaluation. We keep only those attributes which contribute for better adaptation of meaning of the dataset. We have executed the techniques of Recurrent Neural-Network and Seq2Seq models to …
Published in International Journal of Software Computing and Testing · Vol. 6, Issue 1, 2020 · pp. 1–7 Read article
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Brain-Inspired Computing: The Rise of Neuromorphic AI
Abstract: Neuromorphic computing is an emerging computing paradigm that draws inspiration from the structure and operational principles of the human brain. By integrating ideas from neuroscience, computer design, and materials science, neuromorphic systems aim to deliver high-performance, low-power computation that is suitable for smart data processing. Unlike traditional von Neumann architectures, neuromorphic hardware uses massively parallel processing, event driven computation, and adaptive learning. This paper provides an overview of neuromorphic principles, …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 12, Issue 2, 2026 Read article
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Comparison of Back propagation control algorithm with P-Qtheory for power quality improvement using DSTATCOM under steady state condition
Abstract: Providing consumers with high-quality power is the distribution operator's primary goal. Distribution Static Compensator (DSTATCOM), Dynamic Voltage Restorer (DVR), and Unified Power Quality Conditioner (UPQC) are examples of power converter-based custom power devices (CPDs) that are well-known for enhancing the distribution system's power quality. In order to lessen source-side supply power harmonics, DSTACOM is taken into consideration in this work. Any bespoke power device's performance is heavily dependent on the …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 1, 2026 · pp. 25–34 Read article
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Deep Learning with CNNs: A Survey of Techniques and Real-World Applications
Abstract: Convolutional Neural Networks (CNNs) have emerged one of the most powerfully used tools in deep learning, particularly in image and pattern recognition tasks. CNNs are being revolutionized through deep learning resulting in a dominant architecture in computer vision as well as other various domains. This paper provides a comprehensive survey of CNN-based deep learning, its methodologies, regularizations, and computational efficiencies. We also address the challenges and future directions of CNN. …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 2, 2025 · pp. 1–5 Read article
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Research Paper on Handwritten Character Recognition
Abstract: Handwriting recognition is the capacity of a machine to get and decipher penmanship contribution from numerous sources, for example, paper records, photos, touchscreen gadgets, and so on. Handwriting and automatic character recognition are an emerging area of research and find many applications in banks, offices and industries. The main objective of this project is to design an expert system capable of efficiently recognizing a format character of a particular type …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 7, Issue 1, 2021 · pp. 1–5 Read article
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AI-Assisted Conversion and Optimization of Analog-to-Digital Signal Transmission forLow-Power IoT and Edge Devices
Abstract: The booming implementation of Internet of Things (IoT) and edge computing devices is requiring theimplementation of efficient signal transmission mechanisms to balance between performance and energyefficiency. The current paper introduces an AI-assisted conversion and optimization system of the analog-to-digital (A/D) signal transmission, aimed at low-power IoT and edge devices. The given strategy combines both machine learning algorithms and adaptive sampling and quantization methods to optimize the A/D conversion process in …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 11, Issue 2, 2025 Read article
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Predicting User Engagement on Social Media: A Comparative Study of Machine Learning-based Modeling Approaches
Abstract: Abstract Even while mobile social apps are becoming more and more important in people's daily lives, little is known about the elements that motivate users to interact with these apps. The goal of this work is to analyze and define the transition patterns of individual users' in-app actions as a temporally changing action graph. According to our investigation, action graphs are a useful tool for characterizing user behaviour patterns and …
Published in International Journal of Computer Aided Manufacturing · Vol. 11, Issue 2, 2025 · pp. 41–62 Read article
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Region-based Object Detection and Classification using Faster R-CNN
Abstract: With the advent of Deep Learning the machine learning systems are able to recognize and classify objects of interest in an image. Various advancement has been done in the field of object recognition and classification. Our research work focusses on improving the R-CNN, Fast R-CNN, YOLO architecture. The work focused on using Region Proposals Network (RPN) to extract region of interest in an image. RPN outputs an image based on …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 6, Issue 2, 2020 · pp. 22–30 Read article
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SOFT COMPUTING A NEW USE OF SOFT COMPUTING, ARTIFICIAL INTELLIGENCE, FUZZY LOGIC & GENETIC ALGO-RITHM IN BIOINFORMATICS
Abstract: Abstract:Soft registering is make a few dormant in bioinformatics, particularly by producing minimal effort, low exactness (rough), great arrangements. Bioinformatics is an interdisciplinary research zone that is the edge between the natural and computational sciences. Bioinformatics settlement with calculations, databases and data frameworks, web innovations, man-made reasoning and delicate registering, data and calculation hypothesis, basic science, programming building, information mining, picture preparing, demonstrating and recreation, discrete arithmetic, control and framework …
Published in International Journal of Analog Integrated Circuits · Vol. 6, Issue 1, 2020 · pp. 12–26 Read article