Image Segmentation: Principles, Techniques, and Applications (True PDF)

[LeeAndro]

English | 2022 | ISBN: 9781119859031 | 334 pages | True PDF | 137.52 MB

Image SntationSummarizes and improves new theory, methods, and applications of current image sntation approaches, written by leaders in the field

The process of image sntation divides an image into different regions based on the characteristics of pixels, resulting in a simplified image that can be more efficiently analyzed.​

Image sntation has wide applications in numerous fields rag from industry detection and bio-medicine to intelligent transportation and architecture.

<i>Image Sntation: Principles, Techniques, and Applications</i> is an up-to-date collection of recent techniques and methods devoted to the field of computer vision. Covering fundamental concepts, new theories and approaches, and a variety of practical applications including medical imaging, remote sensing, fuzzy clustering, and watershed transform. In-depth chapters present innovative methods developed by the authorssuch as convolutional neural networks, graph convolutional networks, deformable convolution, and model compressionto assist graduate students and researchers apply and improve image sntation in their work.

Describes basic principles of image sntation and related mathematical methods such as clustering, neural networks, and mathematical morphology. Introduces new methods for achieving rapid and accurate image sntation based on classic image processing and machine learning theory. Presents techniques for improved convolutional neural networks for scene sntation, object recognition, and change detection, etc. Highlights the effect of image sntation in various application scenarios such as traffic image analysis, medical image analysis, remote sensing applications, and material analysis, etc.
<i>Image Sntation: Principles, Techniques, and Applications</i> is an essential resource for undergraduate and graduate courses such as image and video processing, computer vision, and digital signal processing, as well as researchers working in computer vision and image analysis looking to improve their techniques and methods.



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