Evolutionary Computer Vision, Image Processing and Pattern Recognition

Potential topics of interest include, but are not only limited to:

1. New theories and methods in different EC paradigms applied to computer vision, image processing and pattern recognition including

Evolutionary algorithms such as genetic algorithms, genetic programming, evolutionary strategies and evolutionary programming;
Swarm Intelligence methods such as particle swarm optimisation, ant colony optimisation, and differential evolution; and
Other approaches such as learning classifier systems, artificial immune systems, evolutionary multi-objective optimisation, evolutionary learning, memetic computing. Cross-fertilization of evolutionary computation and other soft computing techniques such as neural networks and fuzzy systems is also encouraged.

2. Applications of EC and EC-related techniques to computer vision, image processing and pattern recognition, including

Edge detection
Image segmentation
Automatic feature extraction and construction in complex images
Object identification and scene analysis
Object detection and classification
Handwritten digit recognition and detection
Vehicle plate detection
Face detection and recognition
Texture image analysis
Automatic target recognition
Gesture identification and recognition
Robot vision
Signal Processing
Typical pattern recognition tasks such as classification, regression and clustering
Feature selection/construction and dimensionality reduction
Generalisation, transfer learning, and domain adaptation
Medical and bio-medical data analysis