£88.68

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£89 today · all-time low £86 (Jul 2026) · usually the usual

Springer 3D Point Cloud Analysis - Deep Learning Methods Book

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Description

Explore the fundamentals of 3D point cloud technology with this comprehensive guide from Springer. This book provides a detailed introduction to point cloud applications in industry and covers frequently used datasets. Readers can build a strong foundation through an overview of traditional processing methods before advancing to modern deep learning breakthroughs. The text focuses on three essential computer vision tasks: point cloud classification, segmentation, and registration. These processes are fundamental to any system built on point cloud data. Additionally, the book introduces brand-new explainable machine learning methods designed for point cloud learning, offering lightweight approaches for advanced analysis.

Key Features

This Springer publication covers essential computer vision tasks including point cloud classification, segmentation, and registration.

The content provides an overview of traditional point cloud processing methods to help readers build background knowledge quickly.

Learn about recent breakthroughs in deep learning through a comprehensive analysis of point cloud methods from the past few years.

Explore brand-new explainable machine learning methods designed for lightweight point cloud learning applications.

The book introduces various industry applications and the most frequently used datasets for 3D point cloud research.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
11 December 2021
Listed Since
10 September 2021

Barcode

No barcode data available

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