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334 articles for “feature based techniques”
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Urban Flood Hazard Modeling for Noida City
Abstract: This contemporary work unveils the usage of a new methodology to carry out an accurate hazard mapping of urban flood footprints. It is based on wetness transformation. It is a procedure of conversion of multi-spectral-bands into three dimensional feature space. The present study embraces conversion of thematic mapper (TM) imagery of Landsat to a three dimensional array; brightness, wetness and greenness, followed by the technique of change detection to locate …
Published in Journal of Remote Sensing & GIS · Vol. 7, Issue 1, 2016 · pp. 10–26 Read article
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A Hybrid Multi-Physics Ensemble Deep Learning Framework for Simultaneous Prediction of Thermal and Electrical Conductivity in Functional Polymer-Based Nanocomposites
Abstract: Polymer-based nanocomposites have become promising materials for applications in energy storage, flexible electronics, biomedical devices, aerospace components, and advanced engineering because of their tunable thermal and electrical properties. Reliable prediction of these properties is essential for accelerating material design; however, existing analytical models and conventional machine learning techniques often fail to represent the complex interactions among filler characteristics, polymer matrices, processing conditions, and interfacial transport phenomena. This work presents HMEP-Net, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1062–1082 Read article
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Historical Kannada Handwritten Character Recognition using K-Nearest Neighbour Technique
Abstract: AbstractMost of the historical Kannada handwritten documents are preserved in the manuscript preservation center and archaeological department, and these documents are generally degraded in nature and it is very difficult to read and understand the contents in it. Hence, it is very much essential to digitize the historical Kannada handwritten document and recognize its originality of dynasty. The main objective of this paper is to digitize and recognize the historical …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 1, 2019 · pp. 23–29 Read article
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Design of a Multipurpose Ternary Arithmetic Circuit Using CNTFET
Abstract: AbstractIn this paper, a multipurpose ternary arithmetic circuit is presented for ternary processors based on carbon nanotube field effect transistors (CNTFETs). Both addition and subtraction can be performed using same circuit’s configuration, which is the special feature of the proposed circuit. The combination of pseudo and complimentary logic structure are employed to blend the binary and ternary logic techniques. The propagation delay and power delay product are 139.5 pico second …
Published in Journal of Semiconductor Devices and Circuits · Vol. 3, Issue 1, 2016 · pp. 13–24 Read article
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Video Anomaly Detection using Kalman Based Support Vector Technique
Abstract: AbstractThe digital video processing technology has boomed since last many years. The video processing is done using sum of absolute differences and with the image processing block set. We first calculate motion vectors between successive frames and use them to reduce redundant information. The method uses optical flow algorithm to calculate changes in the intensity of the pixels of the images. Median filtering is used for background extraction which is …
Published in Current Trends in Signal Processing · Vol. 8, Issue 2, 2018 · pp. 4–11 Read article
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FoodieHUB: Food Recipe Suggestion Using AI-ML On Web
Abstract: Finding a delicious recipe to cook with limited ingredients at home can be a challenging task. Many individuals struggle to prepare meals using only the ingredients they have on hand, creating uncertainty and limiting options. This project aims to develop a recipe recommendation system that utilizes machine learning algorithms to suggest recipes based on available ingredients, dietary preferences, cuisine types, cooking time, and user ratings. The project utilizes a Gradient …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 01–07 Read article
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Automated Vessel Segmentation of Retinal Vessels using Hybrid Region Information
Abstract: AbstractRecent researches state that the categorization of retinal vessels into artery/vein (A/V) is a critical phase for automating the detection of vascular adjustments and for the calculation of function symptoms related to numerous systemic illnesses which includes diabetes, high blood pressure, and different cardiovascular situations. This paper affords an automatic method for A/V class, primarily based on the evaluation of a graph extracted from the retinal vasculature. The proposed method …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 3, 2018 · pp. 28–36 Read article
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Human Motion Recognition Using Optical Flow Based Particle Filtering
Abstract: ABSTRACTHuman motion recognition has been a significant topic in computer vision due to its numerous applications such as video surveillance, human machine interaction and video retrieval. One core difficulty behind these applications is mechanically identifying low-level actions and high-level activities of concern. This paper presents a technique of automatically identifying the motion accomplished by humans. The speeded up robust features (Optical flow with kinetic energy algorithm) are made use of, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 1, 2018 · pp. 1–9 Read article
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A Comparative Study of Statistical Features for Satellite Images with Natural Images
Abstract: While satellite imaging involves several bands that capture the geographical features, the natural images taken from camera in real world uses RGB model, which is composed of three channels, where each image can store discrete pixels with conventional brightness intensities between 0 and 255. So, the uniqueness of the two imaging techniques is reflected in its bits of every pixel. It is well known that the whole information of an …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 2, 2016 · pp. 59–66 Read article
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CIPHER Intelligence: AI-Powered Global Military Expenditure Analysis and Predictive Modeling
Abstract: Military expenditure analysis has emerged as a critical component of economic and geopolitical intelligence in the modern era. This paper presents CIPHER Intelligence, a comprehensive AI-powered platform for analyzing and predicting global military spending patterns across 211 countries spanning54 years (1970-2024). We employ advanced machine learning techniques, particularly Random Forest regression models, to achieve 99.5% prediction accuracy for military expenditure forecasting based on economic indicators. The platform integrates data from …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 1–8 Read article
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Innovative Eyewear for the Visually Impaired
Abstract: Object detection systems are essential tools for identifying and locating objects within images or videos. When integrated into spectacles or wearable devices, these systems provide users with real-time information about objects present in their surroundings. This functionality serves diverse purposes, such as assisting visually impaired individuals in navigating their environment or offering augmented reality data to workers during tasks. Region-based Convolutional Neural Networks (RCNN) represent a prominent machine learning model …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 1, 2024 · pp. 27–34 Read article
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Automated Fake News Detection System
Abstract: The classification of fake news on social media platforms has drawn a lot of attention recently because it is so simple to put false stuff there. In addition, they prefer social media to traditional television as their news source of choice. These patterns have increased academics' understanding of fake news and inspired an increase in interest in its identification. The primary goal of this work was to classify incorrect information …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 1, 2023 · pp. 70–78 Read article
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OBD-II Big Data–Driven ML and AI-Based Virtual Sensing for Fuel Economy, Component Health, and Carbon Intelligence
Abstract: The rapid growth of connected vehicles has led to the large-scale availability of high-frequency On-Board Diagnostics II (OBD-II) data; however, much of this data remains underutilised, as existing studies and commercial systems typically address fuel economy, maintenance, or emissions in isolation or rely on additional physical sensors. Such fragmented and sensor-dependent approaches limit scalability and increase system cost, particularly in high-volume and resource-constrained vehicle markets. To address this gap, this …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 41–52 Read article
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Cascade of Gait Recognition with Surveillance System in a Client-Server Environment
Abstract: ABSTRACTThis paper presents a system consisting of the application of gait recognition, a physiological biometric applied in a client-server environment. Now-a-days security plays a very important role in almost all fields and most of the public places like banks, airports, railway stations, etc., which require more security as the thieves and criminals are very intelligent whose objective is to create problems for human life and many untoward incidents. The gait …
Published in Journal of Computer Technology & Applications · Vol. 3, Issue 1, 2012 · pp. 26–36 Read article
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Molecular Docking Technique Assisted Discovery of Some Hydroxylated Chalcone Molecules as α-glucosidase Inhibitors
Abstract: The present study involved exploration of the inhibitory potential of some A-ring hydroxylated chalcone compounds against PDB ID: 2QMJ file (Maltase-glucoamylase in complex with acarbose) with the assistance of iGEMDOCK (Genetic Evolutionary Method for Molecular Docking) software. The present study highlighted the immense potentials of several unexplored hydroxyl group (in ring-A) containing chalcones in successfully inhibiting the one of the most effective anti-hyperglycemic based enzymatic target α-glucosidase. The research has …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 6, Issue 1, 2019 · pp. 34–38 Read article
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Ventricular Arrhythmia Detection Techniques for ECG Signal: A Survey Approach
Abstract: Electrocardiogram (ECG) represents the electrical activity of the heart and is used to measure the rate and regularity of heartbeats. In this paper we propose a method for an Independent Component Analysis (ICA) based detection and classification of the ventricular arrhythmia. The malignant ventricular arrhythmia database from www.physionet.org/physiobank/database/vfdb has been utilized for evaluating the algorithm over MATLAB interface. This scheme assimilates ICA and probabilistic neural network for classifying critical arrhythmia …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 5, Issue 1, 2015 · pp. 25–30 Read article
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Performance Analysis of Fusion Classifier of Face Recognition System based on ANN and GA
Abstract: Though a lot of significant work has been done for recognizing and improving the performance in facial pattern, most techniques have been developed based on a single classifier. But most often, the performance of the classifier is not satisfactory in some case. It has been proposed that the performance of face recognition will beimproved by fusing two or more classifiers. We can combine the information/data in different level i.e., feature …
Published in Current Trends in Information Technology · Vol. 4, Issue 1, 2014 · pp. 4–13 Read article
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Fake Cryptocurrency Detection Using Python
Abstract: This study investigates the use of Python-based techniques for detecting fraudulent cryptocurrencies, addressing a growing concern in the digital financial ecosystem. The research methodology integrates various data science approaches, including web scraping, API integration, and advanced data analysis using Pandas and NLTK. Machine learning models, particularly classification algorithms such as Random Forest, are employed to analyze key features extracted from cryptocurrency whitepapers, social media discussions, and transactional data. By training …
Published in Recent Trends in Programming languages · Vol. 12, Issue 1, 2025 · pp. 1–7 Read article
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Crop Yield Prediction Using Machine Learning Algorithm Based on Climate Variables
Abstract: India's economy is based primarily on agriculture, as over 50% of the country's population depends on it for their livelihood. The long-term viability of agriculture is seriously threatened by variations in the weather, climate, and other environmental factors. Because machine learning provides tools for decision assistance in agricultural yield prediction, including guidance on which crops to plant and when to plant them during the growing season, it is essential to …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 49–52 Read article
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Machine Learning-Based Disease Prediction: A Comparative Analysis for Diabetes, Brain Tumor, and Parkinson's Disease
Abstract: This paper presents a web-based disease prediction system that integrates machine learning and deep learning techniques to assist in the early detection of Parkinson’s Disease, Diabetes, and Brain Tumors. By utilizing clinical data and MRI images, the platform provides rapid and interpretable predictions to support proactive health management. Logistic Regression models are applied to classify structured datasets for predicting Parkinson’s disease and Diabetes, making use of their effectiveness in binary …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 44–54 Read article