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Found 5 papers, 1 papers with code
Optimized Deep Feature Selection for Pneumonia Detection: A Novel RegNet and XOR-Based PSO Approach
In this research, an XOR based Particle Swarm Optimization (PSO) is proposed to select deep features from the second last layer of a RegNet model, aiming to improve the accuracy of the CNN model on Pneumonia detection.
Color Image Segmentation Using Multi-Objective Swarm Optimizer and Multi-level Histogram Thresholding
More precisely, this method first combines the objective function of traditional thresholding algorithms to design comprehensive objective functions then uses multi-objective optimizers to find the best thresholds during the optimization of designed objective functions.
Distributed Swarm Collision Avoidance Based on Angular Calculations
We evaluated the proposed approach on various simulation and experimental scenarios and compared the results with FMP and ORCA, two important algorithms in this field.
Multi-agent Motion Planning for Dense and Dynamic Environments via Deep Reinforcement Learning
This paper introduces a hybrid algorithm of deep reinforcement learning (RL) and Force-based motion planning (FMP) to solve distributed motion planning problem in dense and dynamic environments.
Force-based Algorithm for Motion Planning of Large Agent Teams
This paper presents a distributed, efficient, scalable and real-time motion planning algorithm for a large group of agents moving in 2 or 3-dimensional spaces.
