Figure-ground image segmentation using feature-based multi-objective genetic programming techniques
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Summary
The results show that the proposed MOGP methods can evolve solutions with good trade-offs between the functionality and complexity, and INSGP is better at keeping solution diversity than ISPGP for the segmentation tasks in this paper.
- Type
- article
- Published
- 2017-11-08
- Cited by
- 10
- References
- 38
- OpenAlex
- https://openalex.org/W2767881371
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:28027879
Keywords
Computer science, Multi-objective optimization, Evolutionary algorithm, Segmentation, Image segmentation
References
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- Using multi-objective evolutionary algorithms for single-objective constrained and unconstrained optimization
- Multiobjective genetic programming: reducing bloat using SPEA2
- The Pascal Visual Object Classes Challenge: A Retrospective
- Online Glocal Transfer for Automatic Figure-Ground Segmentation
- Deformable Templates Guided Discriminative Models for Robust 3D Brain MRI Segmentation
- Genetic programming based image segmentation with applications to biomedical object detection
- Texture Segmentation by Genetic Programming
- Effects of Code Growth and Parsimony Pressure on Populations in Genetic Programming
- Combined Top-Down/Bottom-Up Segmentation
- Feature Learning for Image Classification Via Multiobjective Genetic Programming
- A fast and elitist multiobjective genetic algorithm: NSGA-II
- A Comparison of Bloat Control Methods for Genetic Programming
- Single and Multi Objective Genetic Programming for software development effort estimation
- Extracting image features for classification by two-tier genetic programming
Cited by
- A recent survey on the applications of genetic programming in image processing
- Preference-driven Pareto front exploitation for bloat control in genetic programming
- Indoor scene segmentation algorithm based on full convolutional neural network
- Bi-objective memetic GP with dispersion-keeping Pareto evaluation for real-world regression
- A Soft Computing Approach for Selecting and Combining Spectral Bands
- Multi-objective genetic programming for feature learning in face recognition
- Bloat-aware GP-based methods with bloat quantification
- A Survey on Evolutionary Computation for Computer Vision and Image Analysis: Past, Present, and Future Trends
- Architecture search of accurate and lightweight CNNs using genetic algorithm
- Multiple-Feature Construction for Image Segmentation Based on Genetic Programming
- Genetic Programming for Supervised Figure-ground Image Segmentation
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