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Decision-level Gait Fusion for Human Identification at a Distance
Published 2014Get full text
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A FUZZY EVOLUTIONARY ALGORITHM FOR TOPOLOGY DESIGN OF CAMPUS NETWORKS
Published 2020“…In this paper, we present a Simulated Evolution algorithm for the design of campus network topology. …”
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem
Published 2002“…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and c cliques. …”
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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm
Published 2020“…The problem consists of deciding the number, types, and locations of the network active elements (hubs, switches, and routers), as well as the links and their capacities. …”
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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm
Published 2020“…The problem consists of deciding the number, types, and locations of the network active elements (hubs, switches, and routers), as well as the links and their capacities. …”
Get full text
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An Optimized Feature Selection Technique in Diversified Natural Scene Text for Classification Using Genetic Algorithm
Published 2021“…First after preprocessing input images, the whole feature space (population) is built using a multimodal feature representation technique. Second, a feature level fusion approach is used to combine the features. …”
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Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network
Published 2024“…Computational techniques, like the finite element method, are used to analyse behaviours based on varied input parameters. …”
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Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information
Published 2019“…This basically follows either a feature-level or decision-level strategy. In all likelihood, while features from several modalities may enhance the classification performance, they might exhibit high dimensionality and make the learning process complex for the most used machine learning algorithms. …”
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Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification
Published 2025“…In this study, we introduce an innovative method for the multi-classification of breast cancer histopathological images utilizing Bidirectional Recurrent Neural Networks (BRNN). The BRNN structure consists of four unique elements: the backbone branch for transfer learning, the Gated Recurrent Unit (GRU), the residual collaborative branch, and the feature fusion module. …”
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Fuzzy simulated evolution algorithm for topology design of campusnetworks
Published 2000“…We present an approach based on the simulated evolution algorithm for the design of campus network topology. …”
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Intelligent Rapidly-Exploring Random Tree Star Algorithm
Published 2024Get full text
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Collision-Free Autonomous Navigation Solution for Mobile Wheeled
Published 2023Get full text
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Nonlinear analysis of shell structures using image processing and machine learning
Published 2023“…We show that the results of the trained network agree well with the results of the nonlinear finite element analysis. …”
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Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms
Published 2021“…A machine learning classification pipeline is developed using multi-domain feature extraction (time, frequency, time-frequency), feature selection (Gini impurity), classifier design, and score level fusion. Different classifiers were trained, validated, and tested for two different classification experiments - personalized and generalized. …”
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Content-Aware Adaptive Video Streaming Using Actor-Critic Deep Reinforcement Learning
Published 2024Get full text
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Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV
Published 2013Get full text
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The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions
Published 2022“…To this end, we carefully identify the types of DRL algorithms utilized in each related work, the elements of these algorithms, and the main findings of each related work. …”