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Can I read Genetic Learning For Adaptive Image Segmentation (the Springer International Series In Engineering And Computer Science) on EtoBox?

Genetic Learning For Adaptive Image Segmentation (the Springer International Series In Engineering And Computer Science) by Bir Bhanu, Sungkee Lee (auth.) is a nonfiction available to read on EtoBox.

What is Genetic Learning For Adaptive Image Segmentation (the Springer International Series In Engineering And Computer Science) about?

Image segmentation is generally the first task in any automated image understanding application, such as autonomous vehicle navigation, object recognition, photointerpretation, etc. All subsequent tasks, such as feature extraction, object detection, and object recognition, rely heavily on the quality of segmentation. One of the fundamental weaknesses of current image segmentation algorithms is their inability to adapt the segmentation process as real-world changes are reflected in the image. Only after numerous modifications to an algorithm's control parameters can any current image segmentation technique be used to handle the diversity of images encountered in real-world applications. __Genetic Learning for Adaptive Image Segmentation__ presents the first closed-loop image segmentation system that incorporates genetic and other algorithms to adapt the segmentation process to changes in image characteristics caused by variable environmental conditions, such as time of day, time of year, weather, etc. Image segmentation performance is evaluated using multiple measures of segmentation quality. These quality measures include global characteristics of the entire image as well as local

Who reads Genetic Learning For Adaptive Image Segmentation (the Springer International Series In Engineering And Computer Science)?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Bir Bhanu, Sungkee Lee (auth.)
Publisher
Springer Science+Business Media, LLC
Published
1994
Language
EN
ISBN
9780792394914
Category
nonfiction
Subjects
Technology, Engineering, Computer Science

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