Neural networks for HREM image analysis

被引：7

作者：

Kirschner, H ^{[1
]}

Hillebrand, R ^{[1
]}

机构：

[1] Max Planck Inst Microstruct Phys, D-06120 Halle, Germany

来源：

INFORMATION SCIENCES | 2000年 / 129卷 / 1-4期

关键词：

neural network; image processing; electron microscopy; compound semiconductor;

D O I：

10.1016/S0020-0255(00)00067-0

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We present a new neural network-based method of image processing for determining the local composition and thickness of III-V semiconductors in high resolution electron microscope images. This is of great practical interest as these parameters influence the electrical properties of the semiconductor. Neural networks suppress correlated noise from amorphous object covering and distinguish between variations of sample thickness and semiconductor composition. (C) 2000 Elsevier Science Inc. All rights reserved.

引用

页码：31 / 44

页数：14

共 16 条

[1]

[Anonymous], [No title captured]

[2] Fuzzy logic approaches to the analysis of HREM images of III-V compounds [J].

Hillebrand, R .

JOURNAL OF MICROSCOPY, 1998, 190 :61-72

[3] A fuzzy logic approach to edge detection in HREM images of III-V crystals [J].

Hillebrand, R ;

Wang, PP ;

Gosele, V .

INFORMATION SCIENCES, 1996, 93 (3-4) :321-338

[4]

HILLEBRAND R, 1996, P WORKSH BREAKTHR OP, P77

[5]

HILLEBRAND R, 1997, P 3 JOINT C INF SCI, V1, P55

[6]

Jollife I., 1986, Principal Component Analysis

[7]

KIRSCHNER H, 1997, THESIS U REGENSBURG

[8]

KIRSCHNER H, 2000, THESIS M LUTHER U HA

[9]

KIRSCHNER H, 1997, OPTIK S, P74

[10] AN APPROACH TO QUANTITATIVE HIGH-RESOLUTION TRANSMISSION ELECTRON-MICROSCOPY OF CRYSTALLINE MATERIALS [J].

KISIELOWSKI, C ;

SCHWANDER, P ;

BAUMANN, FH ;

SEIBT, M ;

KIM, Y ;

OURMAZD, A .

ULTRAMICROSCOPY, 1995, 58 (02) :131-155

← 1 2 →