FEATURE DIMENSION REDUCTION FOR EFFICIENT MEDICAL IMAGE RETRIEVAL SYSTEM USING UNIFIED FRAMEWORK

Some population based heuristic such as Memetic Algorithm [9], Ant Colony Optimization (ACO) [10], Particle Swarm Optimization [12], meta-heuristic such as Simulated Annealing [19],

Swarm Optimization ) e HAP ( Hybrid Ant Colony and Particle Swarm ), sob a forma de ACO(T)-H, ACO(T)-HD, ACO(S)-H, ACO(S)-HD, PSO-H, PSO-HD, HAP-H e HAP-HD, onde os índices

Popular optimization techniques, as genetic algorithm (GA) and particle swarm optimization (PSO), were used to design the shape of the ground plane in order to improve

Query Image and/or Database Image Extract Metadata from xml files of all the database images Text Feature vector Image Feature Vector Text matching using cosine

The techniques discussed in this paper are Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Bacterial Foraging Optimization Algorithm (BFOA),

has to deal with the difficulties existing in single object tracking, such as changing appearances, non-rigid motion, dynamic illumination and occlusion, as well

A new IPSO-SA algorithm based on an improved particle swarm optimization and a modified simulated annealing was proposed to find the cardinality constrained efficient frontier.

Once the weights and biases are found using Particle swarm optimization (PSO) with neural network used as training algorithm for specified epoch, the same are used to train the