Metallographic and Materialographic Specimen Preparation, Light Microscopy, Image Analysis, and Hardness Testing

Metallographic and Materialographic Specimen Preparation, Light Microscopy, Image Analysis, and Hardness Testing
Author :
Publisher : ASTM International
Total Pages : 761
Release :
ISBN-10 :
ISBN-13 :
Rating : 4/5 ( Downloads)

Book Synopsis Metallographic and Materialographic Specimen Preparation, Light Microscopy, Image Analysis, and Hardness Testing by :

Download or read book Metallographic and Materialographic Specimen Preparation, Light Microscopy, Image Analysis, and Hardness Testing written by and published by ASTM International. This book was released on with total page 761 pages. Available in PDF, EPUB and Kindle. Book excerpt:


Metallographic and Materialographic Specimen Preparation, Light Microscopy, Image Analysis, and Hardness Testing Related Books

Metallographic and Materialographic Specimen Preparation, Light Microscopy, Image Analysis, and Hardness Testing
Language: en
Pages: 761
Metallographic and Materialographic Specimen Preparation, Light Microscopy, Image Analysis and Hardness Testing
Language: en
Pages:
Authors:
Categories: Metallographic specimens
Type: BOOK - Published: 2007 - Publisher:

DOWNLOAD EBOOK

Metallography in Archaeology and Art
Language: en
Pages: 293
Authors: David A. Scott
Categories: Technology & Engineering
Type: BOOK - Published: 2019-08-30 - Publisher: Springer Nature

DOWNLOAD EBOOK

This book provides a comprehensive introduction to the metallographic study of ancient metals. Metallography is important both conceptually as a microstructural
American Book Publishing Record
Language: en
Pages: 838
Authors:
Categories: American literature
Type: BOOK - Published: 2007 - Publisher:

DOWNLOAD EBOOK

Content-based Microscopic Image Analysis
Language: en
Pages: 198
Authors: Chen Li
Categories: Computers
Type: BOOK - Published: 2016-05-15 - Publisher: Logos Verlag Berlin GmbH

DOWNLOAD EBOOK

In this dissertation, novel Content-based Microscopic Image Analysis (CBMIA) methods, including Weakly Supervised Learning (WSL), are proposed to aid biological