Search alternatives:
method algorithm » mould algorithm (Expand Search)
data fitting » data mining (Expand Search), data hiding (Expand Search)
tracking » training (Expand Search), taking (Expand Search)
method algorithm » mould algorithm (Expand Search)
data fitting » data mining (Expand Search), data hiding (Expand Search)
tracking » training (Expand Search), taking (Expand Search)
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Radar Pulse Interleaving For Multi-Target Tracking
Published 2020“…Interleaving algorithms developed to operate radars exploit the dead-times between the transmitted and the received pulses to allocate new tracking tasks that might involve transmitting or receiving pulses, thus increasing the capacity of the system. …”
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Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm
Published 2023Subjects: Get full text
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Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques
Published 2024“…This paper presents two different methods for track-to-track fusion of drone tracks. The sensors are unbiased radars with fixed locations. …”
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Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem
Published 2023“…In many cases, several radars are collectively used to track drones efficiently, generating measurements and several tracks under different circumstances. …”
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
Published 2016Subjects: Get full text
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Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization
Published 2024“…This paper presents a novel hybrid optimization method to solve the resource allocation problem for multi-target multi-sensor tracking of drones. This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. …”
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Genetic and heuristic algorithms for regrouping service sites. (c2000)
Published 2000Get full text
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masterThesis -
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A reduced model for phase-change problems with radiation using simplified PN approximations
Published 2025“…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …”
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Brain Source Localization in the Presence of Leadfield Perturbations
Published 2015Get full text
doctoralThesis -
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Monitoring Bone Density Using Microwave Tomography of Human Legs: A Numerical Feasibility Study
Published 2021“…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …”
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Design of adaptive arrays based on element position perturbations
Published 1993“…The main advantage of using this technique over the other commonly used methods is that the amplitudes and phases of the array elements can be used mainly to steer the main beam towards the desired signal. …”
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Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization
Published 2023“…In this work, one radar and one camera collaborate to generate tracks of a drone. …”
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The Use of Microwave Tomography in Bone Healing Monitoring
Published 2019Get full text
doctoralThesis -
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A Novel Genetic Algorithm Optimized Adversarial Attack in Federated Learning for Android-Based Mobile Systems
Published 2025“…<p dir="ltr">Federated Learning (FL) is gaining traction in Android-based consumer electronics, enabling collaborative model training across decentralized devices while preserving data privacy. However, the increasing adoption of FL in these devices exposes them to adversarial attacks that can compromise user data and device security. …”
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Bee Colony Algorithm for Proctors Assignment.
Published 2015“…The search accomplished by three types of bees over a number of iterations aiming to find the source with the highest nectar value (fitness value of a candidate solution). We apply the Bee Colony algorithm to previously published data. …”
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