A Compact Genetic Algorithm with Elitism and Mutation Applied to Image Recognition

A new approach for template matching in digital images using an Artificial Bee Colony Algorithm

“…In the next experiment, we have used a real-world grayscale image ( fig. 3(a) and 3(b)) with the objective of comparing the performance of ABC with other algorithms: PSO [13] and emCGA [14]. Table 4 shows the results obtained by the algorithms in which ESA represents an Exhaustive Search Algorithm.…”

“…This fact suggests the use of fast algorithms based on metaheuristics. For instance, Silva et al [14], applied a Compact Genetic Algorithm (CGA) with elitism and mutation (emCGA) to object recognition problem. Results showed that the method can be efficiently applied to practical situations without additional computational costs.…”

A compact compound sinusoidal differential evolution algorithm for solving optimisation problems in memory-constrained environments

“…The used algorithm Image recognition (Silva et al, 2008) emCGA Gray image segmentation (Zhao, 2020) cCSO Robotics (Iacca et al, 2012a) cDE-light (Neri et al, 2011) DEcDE (Lachouri et al, 2016) cHAS cFO (Tighzert et al, 2018) a family of real-valued cFA algorithms Evolvable hardware (Aporntewan & Chongstitvatana, 2001) cGA (Gallagher & Vigraham, 2002), (Gallagher et al, 2004) new cGA alternatives by introducing some modifications namely elitism, mutation and resampling (Jewajinda & Chongstitvatana, 2008) Compact cellular GA Online control design of a boiler (Neri et al, 2013b) cPSO Precision motion control (Mininno et al, 2011) cDE Road traffic management (Olarthichachart et al, 2010) cGA Optimisation of the pipeline network (Afshar, 2009) (Azouaoui et al, 2012) cGA, OCGAD (Shakeel, 2010) cGA (Xing & Qu, 2012) pe-cGA with three extensions Bioinformatics (Badr et al, 2008) modified pe-cGA (Huang et al, 2005) MCGA Heterogeneous systems/grids (Sahu & Satav, 2012) cGA (Kumar Singh & Sahli, 2014) Web semantics (Xingsi et al, 2017) cGA Embedded systems (Timmerman, 2012) cGA Artificial neural networks (Yang et al, 2018) cTLBO Deep learning (Paul et al, 2019) cGA Hydroelectric power generation (Tian et al, 2020) CPIO Optimal 3D path planning of underwater unmanned submersibles (Song et al, 2020) cCS, pcCS…”

Bee Colony Algorithm application for manipulating metalcastings in SME

“…They have been applied to several real world combinatorial problems in manufacturing. For example, Silva, Lopes and Lima [20] as well as Perlin, Lopes and Centeno [15] presented two metaheuristic approaches, one based on compact Genetic Algorithm (CGA) and the other based on Particle Swarm Optimization (PSO). Results show that both methods can be efficiently applied to practical situations with reasonable computational costs.…”