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1
Spatially-Distributed Missions With Heterogeneous Multi-Robot Teams
Published 2021“…Both combine a generic MILP solver and a genetic algorithm, resulting in efficient anytime algorithms. …”
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CoLoSSI: Multi-Robot Task Allocation in Spatially-Distributed and Communication Restricted Environments
Published 2024“…<p dir="ltr">In our research, we address the problem of coordination and planning in heterogeneous multi-robot systems for missions that consist of spatially localized tasks. Conventionally, this problem has been framed as a task allocation problem that maps tasks to robots. …”
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Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification
Published 2025“…<p dir="ltr">In recent years, deep learning methods have dramatically improved medical image analysis, though earlier models faced difficulties in capturing intricate spatial and contextual details. …”
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
Published 2016Get full text
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5
STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization
Published 2025“…In this paper, a novel speech separation algorithm is proposed that integrates the twin-delayed deep deterministic (TD3) policy gradient reinforcement learning (RL) agent with the expectation maximization (EM) algorithm for clustering the spatial cues of individual sources separated on azimuth. …”
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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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Spectrum Sensing Algorithms for Cooperative Cognitive Radio Networks
Published 2010Get full text
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9
MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network
Published 2022“…Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. Although a few deep learning-based models have been proposed for the removal of ocular, muscle, and cardiac artifacts from EEG data to the best of our knowledge, there is no attempt has been made in removing motion artifacts from motion-corrupted EEG signals: In this paper, a novel 1D convolutional neural network (CNN) called multi-layer multi-resolution spatially pooled (MLMRS) network for signal reconstruction is proposed for EEG motion artifact removal. …”
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Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction
Published 2025“…It is noted that spatial relationships within molecules are crucial in predicting hERG blockers. …”
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A Novel BIPV Reconfiguration Algorithm for Maximum Power Generation under Partial Shading
Published 2020“…The system is optimised for maximum yield to determine the optimal configuration and number of modules for each string using a genetic algorithm. The outcomes from the algorithm are based on clustering the solar insolation values and then applying a genetic algorithm optimisation to indicate the optimum BIPV array layout for maximum yield.…”
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Properties of Unique Degree Sequences of 3-Uniform Hypergraphs
Published 2021“…The existence of this hypergraph makes us conjecture an extended generating algorithm for the sequences of Deza et al. to include a much wider class of unique 3-uniform hypergraphs. …”
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Socially Motivated Approach to Simulate Negotiation Process
Published 2014Get full text
doctoralThesis -
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A reduced model for phase-change problems with radiation using simplified PN approximations
Published 2025“…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. A Newton-based algorithm is also adopted for solving the nonlinear systems resulting from the considered monolithic approach. …”
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Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network
Published 2024“…<p dir="ltr">This study examines the use of injection moulding to evaluate mechanical properties in plastic products, such as shear and residual stresses. …”
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Image-Based Air Quality Estimation Using Convolutional Neural Network Optimized by Genetic Algorithms: A Multi-Dataset Approach
Published 2025“…To mitigate overfitting, we implemented dropout layers, batch normalization, and early stopping, significantly enhancing the model’s generalization capability. Specifically, three different open-access datasets were combined into a single training dataset, capturing extensive temporal, spatial, and environmental variability. …”
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Brain Source Localization in the Presence of Leadfield Perturbations
Published 2015Get full text
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19
Geographical Area Network—Structural Health Monitoring Utility Computing Model
Published 2019“…Every gateway is routing the data to SHM-UCM servers running a geo-spatial patch health assessment and prediction algorithm. …”
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Acoustic Based Localization of Partial Discharge Inside Oil-Filled Transformers
Published 2022“…They are reachable if needed to be repaired or replaced. Several numerical studies have been carried out considering different PD source positions, and the Levenberge-Marquardt algorithm is employed for solving localization equations.…”