Andere Kunden interessierten sich auch für
![Artificial Bee Colony Algorithm With Mutation (ABCM)using Modified Sea]( "Artificial Bee Colony Algorithm With Mutation (ABCM)using Modified Sea")
Artificial Bee Colony Algorithm With Mutation (ABCM)using Modified Sea27,99 €![A Hybrid Best-So-Far Artificial Bee Colony Algorithm]( "A Hybrid Best-So-Far Artificial Bee Colony Algorithm")
A Hybrid Best-So-Far Artificial Bee Colony Algorithm26,99 €![Content-Based Image Retrieval]( "Content-Based Image Retrieval")
Content-Based Image Retrieval74,99 €![SIFT & SURF on GPUs for Feature Extraction]( "SIFT & SURF on GPUs for Feature Extraction")
SIFT & SURF on GPUs for Feature Extraction23,99 €![Exploration of fusion-based approach for building a robust CBIR system]( "Exploration of fusion-based approach for building a robust CBIR system")
Exploration of fusion-based approach for building a robust CBIR system36,99 €![Content based Image Retrieval System Using Machine Learning]( "Content based Image Retrieval System Using Machine Learning")
Content based Image Retrieval System Using Machine Learning30,99 €![CONTENT BASED IMAGE RETRIEVAL WITH FEEDBACK TECHNIQUE]( "CONTENT BASED IMAGE RETRIEVAL WITH FEEDBACK TECHNIQUE")
CONTENT BASED IMAGE RETRIEVAL WITH FEEDBACK TECHNIQUE26,99 €
This book highlights a new hybrid technique that is dependent on artificial bee colony (ABC) and k-means algorithms to retrieve the most similar image to the image query. ABC algorithm guaranty an optimized clustering for the contents (Color and Texture: extracted using common methods) of images. The new technique is applied on set of images (Wang dataset), where it showed high positive result in term of retrieval precision.