Showing 1 - 20 results of 30 for search '(((( table 1_decoding algorithm ) OR ( radar tracking algorithm ))) OR ( element data algorithm ))', query time: 0.15s Refine Results
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    Radar Pulse Interleaving For Multi-Target Tracking by Elshafei, M.

    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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    article
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    Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques by Fares, Samar

    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 by Abu Zitar, Raed

    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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    Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

    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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    Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

    Published 2023
    “…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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    Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization by De Rochechouart, Maxence

    Published 2023
    “…In this work, one radar and one camera collaborate to generate tracks of a drone. …”
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    XBeGene: Scalable XML Documents Generator by Example Based on Real Data by Harazaki, Manami

    Published 2012
    “…Inspired by the query-by-example paradigm in information retrieval, Our generator system i)allows the user to provide her own sample XML documents as input, ii) analyzes the structure, occurrence frequencies, and content distributions for each XML element in the user input documents, and iii) produces synthetic XML documents which closely concur, in both structural and content features, to the user's input data. …”
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    A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai by ALGHANEM, HANI SUBHI MOHD

    Published 2024
    “…The proposed framework comprises key elements: Important Decisions derived from interviews with transportation leaders, Knowledge Management enhanced by AI algorithms, Data Mining/Analysis utilizing historical data, the Fleet Management System employing Oracle ERP, and a Data-Driven Decision Support Framework that leans towards the extended framework approach. …”
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    Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

    Published 2023
    “…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”
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    Correlation Clustering with Overlaps by Fakhereldine, Amin

    Published 2020
    “…Moreover, we allow the new vertex splitting operation, which allows the resulting clusters to overlap. In other words, data elements (or vertices) will be allowed to be members in more than one cluster instead of limiting them to only one single cluster, as in classical clustering methods. …”
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    Recursive Parameter Identification Of A Class Of Nonlinear Systems From Noisy Measurements by Emara-Shabaik, Husam

    Published 2020
    “…The model structure is made up of two linear dynamic elements separated by a nonlinear static one. The nonlinear element is assumed to be of the polynomial type with known order; The identification is based on input/output data where the output is contaminated with measurement noise. …”
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    A hybrid approach for XML similarity by Tekli, Joe

    Published 2007
    “…Various algorithms for comparing hierarchically structured data, e.g. …”
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