Bayesian genetic programming for edge detection

Feature Extraction in Edge Detection using Genetic Programming

Edge detection is important in image processing. Extracting edge features is the main and necessary process in edge detection. Since features in edge detection are implicit, most of the existing edge features only work well on specific images. Using a moving window has a trade-off between noise rejection and localisation accuracy. Genetic Programming (GP) has been widely applied to image proces...

Bayesian Genetic Programming

Genetic Programming for Object Detection

This paper examines genetic programming as a machine learning technique in the context of object detection. Object detection is performed on image features and on gray-scale images themselves, with different goals. The generality of the solutions discovered, over the training set and over a wider range of images, is tested in both cases. Using genetic programming as a means of testing the utili...

Evolving Edge Detectors with Genetic Programming

Edge detection is the process of detecting discontinuities in signals and images. We apply genetic programming techniques to the production of highperformance edge detectors for 1-D signals and image profiles. The method, which it is intended to extend to the development of practical edge detectors for use in image processing and machine vision, uses theoretical performance measures as criteria...

islanding detection methods for microgrids

امروزه استفاده از منابع انرژی پراکنده کاربرد وسیعی یافته است . اگر چه این منابع بسیاری از مشکلات شبکه را حل می کنند اما زیاد شدن آنها مسائل فراوانی برای سیستم قدرت به همراه دارد . استفاده از میکروشبکه راه حلی است که علاوه بر استفاده از مزایای منابع انرژی پراکنده برخی از مشکلات ایجاد شده توسط آنها را نیز منتفی می کند . همچنین میکروشبکه ها کیفیت برق و قابلیت اطمینان تامین انرژی مشترکان را افزایش ...