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Proceedings International Workshop on Mobile Mapping Technology

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fullscreen: Proceedings International Workshop on Mobile Mapping Technology

Monograph

Persistent identifier:: 856671290

Author:: Li, Rongxing

Title:: Proceedings International Workshop on Mobile Mapping Technology

Sub title:: April 21 - 23, 1999, Bangkok, Thailand

Scope:: 1 Online-Ressource (Getr. Zählung [ca. 400 Seiten])

Year of publication:: 1999

Place of publication:: London

Publisher of the original:: RICS Books

Identifier (digital):: 856671290

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: [Poster Session (1) on Airborne & Spaceborne Remote Sensing (JARS)]

Document type:: Monograph

Structure type:: Chapter

Chapter

Title:: GENERALIZATION TECHNIQUES FOR LAYERED NEURAL NETWORKS IN THE CLASSIFICATION OF REMOTELY SENSED IMAGES. Eihan SHIMIZU and Morito TSUTSUMI, Le Van TRUNG.

Document type:: Monograph

Structure type:: Chapter

Proceedings International Workshop on Mobile Mapping Technology
Cover
ColorChart
Title page
Title page
Proceedings of International Workshop on Mobile Mapping Technology April 21-23, 1999, Maruay Garden Hotel, Bangkok, Thailand
Greeting from Bangkok.
PREFACE.
On behalf of the International Association of Geodesy (IAG) Working Group [...]
TECHNICAL PROGRAM.
[Session 1: Mobile Mapping (1)]
A ROBUST METHOD FOR REGISTERING 2.5D LASER RANGE IMAGES OF URBAN OBJECTS. Huijing ZHAO, Ryosuke SHIBASAKI.
AN INTELLIGENT MOBILE MAPPING SYSTEM. Naser El-Sheimy, Mike Chapman, and C. Tao.
A Mobile Mapping System Based on GPS, GIS and Multi-sensor. Deren Li.
AIRPORT DATA BASIS FOR TAGSY GUIDANCE SYSTEMS. W. Möhlenbrink, R. Bettermann.
INTEGRATING TECHNOLOGIES: DGPS, DEAD RECKONING AND MAP MATCHING. T. A. Hailes.
[Session 2: Mobile Mapping (2)]
FILTERALGORITHMS FOR OPTIMAL DETERMINATION OF POSITION AND ATTITUDE OF THE MOBILE MAPPING SYSTEM KISS. H. Sternberg, W. Caspary and H. Heister.
DEVELOPMENT OF AN INTEGRATED SYSTEM FOR MAPPING ROAD WIDTH USING DIGITAL VIDEO AND GLOBAL POSITIONING SYSTEM. Shanmugam Ganeshkumar, Kiyoshi HONDA, Shunji MURAI.
DIRECT PLATFORM ORIENTATION IN AERIAL AND LAND-BASED MAPPING PRACTICE. Dorota A. Grejner-Brzezinska, Charles K. Toth and Edward Oshel.
TOWARDS AUTOMATED PROCESSING OF MOBILE MAPPING IMAGE SEQUENCES. C. Tao, M. A. Chapman, and N. El-Sheimy, B. Chaplin.
[Poster Session (1) on Airborne & Spaceborne Remote Sensing (JARS)]
Generation of Digital Elevation Model derived from JERS1 SAR Interferometry. Mitsuharu TOKUNAGA.
GENERALIZATION TECHNIQUES FOR LAYERED NEURAL NETWORKS IN THE CLASSIFICATION OF REMOTELY SENSED IMAGES. Eihan SHIMIZU and Morito TSUTSUMI, Le Van TRUNG.
THE CRANES' NESTING ANALYSIS USING GIS - LANDSCAPE ECOLOGICAL APPLICATIONS -. Koichi HIRATA, Hiroshi MURAKAMI.
INTERPRETABILITY OF GEOGRAPHIC INFORMATION FROM HIGH RESOLUTION SATELLITE IMAGES. Toshiaki Hashimoto.
Reassessment of Todaro's Migration Model to Incorporate Socioeconomic and Natural Resource Environment by Using Remote Sensing and GIS: A Case of Thailand. Bhuwneshwar Prasad SAH, Eihan SHIMIZU and Morito TSUTSUMI.
LAND COVER OF ASIA. Ryutaro Tateishi.
Development of Drain Direction Model based onGTOPO30 and Global Data Sets. Shiro Ochi and Ryosuke Shibasaki.
[Session 3: Kinematic Real-time Positioning]
Positioning Principles and Accuracy of Airborne Laser- Ranging & Multispectral-lmaging Mapping System. Liu Shaochuang, You Hongjian, Xiang Maosheng, Liu Tong, Li Shukai.
Accuracy Assessment and Improvement for Level Survey using Real Time Kinematic (RTK) GPS. Dinesh Manandhar, Kiyoshi Honda, Shunji Murai, Sachio Kubo, Masahiro Yonemura.
Airborne Mapping System with GPS-supported Aerotriangulation. Deren Li, Xiuxiao Yuan.
[Session 4: Sensor Integration and Calibration]
The Calibration of Imaging Sensors Integrated into a Rapid Route Mapping System. C. S. Fraser, A. M. Judd.
CALIBRATING A ZOOM LENS CCD CAMERA FOR A TERRESTRIAL IMAGE BASED SURVEY SYSTEM. Y. D. Huang and D. Chen.
METHOD FOR ACCURATE CAMERA ORIENTATION FOR AUTOMOBILE PHOTOGRAMMETRIC SYSTEM. V. A. Knyaz, S. Yu. Zheltov.
MULTI-SENSOR MAP MATCHING CONCEPTS FOR POSITIONING OF ROAD AND RAIL VEHICLES. R. Czommer, W. Möhlenbrink.
SENSOR INTEGRATION AND CALIBRATION OF DIGITAL AIRBORNE THREE-LINE CAMERA SYSTEMS. Michael Cramer, Dirk Stallmann and Norbert Haala.
[Session 5A: Applications (1)]
Application of Photogrammetric Image Data for Roadway Construction. Guangping He.
SURVEYING AND MAPPING OF URBAN STREETS BY PHOTOGRAMMETRIC TRAVERSE. A. R. SILVA, J. C. BATISTA, R. A. OLIVEIRA, P. O. CAMARGO and J. F. C. SILVA.
[Session 5B: Real-time Imaging (ARIDA)]
ESTIMATION OF ACCURACY OF AIRBORNE LASER PROFILING. Koukichi Kimura, Teruvoshi Fujiwara, Yukihide Akiyama.
CRACK SITUATION GRASP OF DIGITAL IMAGE METHOD. Tatuhide NAKANE, Hisasi TAKAGI, Masaharu OZAWA.
Mobile Mapping Technologies for Safety Driving Assistance in ITS. Yutaka Shimogaki, Tooru Kitagawa, Yoshiki Yamano, Katunori Takahashi.
[Session 6A: Applications (2)]
Virtual Reality Model Created from Mobile Mapping Data as Interface to GIS. Krzysztof Gajdamowicz.
IMPROVED DEM EXTRACTION TECHNIQUES - COMBINING LIDAR DATA WITH DIRECT DIGITAL GPS/INS ORIENTED IMAGERY. Charles K. Toth and Dorota A. Grejner-Brzezinska.
Focal Plane Image Assembly of Subpixel. Si-Dong Zhong, Tian chan Mei.
[Session 6B: Real-time Imaging (ARIDA)]
A Tracking System for Construction vehicles with DGPS and RTK-GPS. Shun'ichi OHTSU, Tomonori TAKADA, Tatsunori SADA.
A METHOD OF ROAD REPRESENTATION IN 3D MAPPING TECHNOLOGY. Tsukasa Hosomura.
Fundamental Study on Ground-Based Sensor Integration for Spatial Data Acquisition. Mitsunori YOSHIMURA, Tetsuji ANAI, Hirofumi CHIKATSU, Ryosuke SHIBASAKI.
Fundamental Study on Development and Application of the Local Positioning System using Accelerometer and Gyroscope. Toshio KOIZUMI, Yasuyuki SHIRAI, Atsuro TAKEMOTO.
[Poster Session (2) on Imaging Sensing (ARIDA)]
THE METHOD OF Field INVESTIGATIONS USING DIGITAL IMAGE. Toshiaki Taguchi, Kosuke Tsuru, Hirofumi Chikatsu.
PERFORMANCE OF ARTIFICIAL RETINA CAMERA AND ITS APPLICATION. Yoichi KUNII, Hirofumi CHIKATSU.
MOTION ANALYSIS ON THE CONSTRUCTION PLANT USING SEQUENTIAL IMAGES. Sosuke YOSHIDA, Hirofumi CHIKATSU.
AUTO-TRACKING AND 3D MEASUREMENT FOR MOVING OBJECT USING VIDEO THEODOLITE. Tsutomu KAKIUCHI, Hirofumi CHIKATSU.
Generation of 3D View Map Using by Raster Base Data Processing. Kunihiko Ono, Shunji Murai, Vivarad Phonekeo and Shigetaka Yasue.
REMAPPING OF HISTORICAL MAPS USING MATHEMATICAL MORPHOLOGY AND ITS APPLICATION. Nobuhiro YAMADA, Hirofumi CHIKATSU.
A Comparative Study on Techniques for Optical Flow Estimation : On the Application to Vehicle Motion Analysis. Takashi FUSE and Eihan SHIMIZU.
Dynamic Analysis of Human Motion using Digital Video Camera mounted on Video Theodolite. Tetsuji ANAI, Hirofumi CHIKATSU.
A New Measurement System of Settlement At Airports Using GPS and Laser Level. Bunji Shigematsu.
[Session 7A: Automatic Object Extraction and Recognition]
INTEGRATION OF FEATURE AND SIGNAL MATCHING FOR OBJECT SURFACE EXTRACTION. Pakom Apaphant, James Bethel.
FEATURE EXTRACTION FROM MOBILE MAPPING IMAGERY SEQUENCES USING GEOMETRIC CONSTRAINTS. Fei Ma and Ron Li.
A MULTILAYER HOPFIELD NEURAL NETWORK FOR 3-D OBJECT RECOGNITION. Zhuowen Tu and Ron Li.
DATABASE GUIDED VERIFICATION AND UPDATING OF TRANSPORTATION OBJECTS WITH VERTICAL LINE FEATURES FROM MOBILE MAPPING IMAGE SEQUENCES. C. Tao.
Traffic Sign Detection from Image Sequences. W. B. Tong, J. Y. Hervé, P. Cohen.
ROBUSTNESS TEST TO OBJECT POSITIONING IN PROJECTIVE SPACE. Xingwen Wang, Deren Li.
[Session 7B: Mobile Mapping for Spatial Data Acquisition]
AUTOMATIC MEASUREMENT OF ROAD WIDTHS IN COLOUR STEREO SEQUENCES ACQUIRED BY A MOBILE MAPPING SYSTEM. Krzysztof Gajdamowicz.
Wearable Computing, Wireless Communication & Knowledge Discovery for Mobile Data Acquisition & Analysis. Klaus Brinkkötter-Runde and Ubbo Visser.
Development of a Low-Cost DGPS/DR System for Vehicle Tracking. Xiufeng He, Thor I. Fossen and Yongqi Chen.
OFF Method and Its Practice on Airborne GPS Data Processing for Photogrammetry. Chen Xiaoming, Liu Jiyu, Li Deren.
List of Registered Participants
Cover

Full text

GENERALIZATION TECHNIQUES FOR LAYERED NEURAL NETWORKS
IN THE CLASSIFICATION OF REMOTELY SENSED IMAGES
Eihan SHIMIZU and Morito TSUTSUMI
Department of Civil Engineering
University of Tokyo
Japan
shimizu@planner.t.u-tokyo.ac.jp , tsutsumi@planner.t.u-tokyo.ac.jp
Le Van TRUNG
Department of Civil Engineering
The National University of Hochiminh City
Vietnam
trung.lv@ut-hcmc.cinetvn.com
KEY WORDS: Layered neural network, generalization, Akaike’s Information Criterion, Tikhonov’s regularization.
ABSTRACT
In recent years, researchers have paid a lot of attention to Layered Neural Networks (LNNs) as a non-parametric approach for the classi
fication of remotely sensed images. This paper focuses on the generalization capability of LNNs, that is, how well an LNN performs with
unknown data. First, we clarify its description from the point of view of information statistics. With this discussion, we provide a fea
sible technique to design the LNN in consideration of its generalization capability. Finally, we apply the proposed technique to a practi
cal land cover classification using remotely sensed images, and demonstrate its potential.
1 INTRODUCTION
Among supervised classification methods for remotely sensed
data, Maximum Likelihood Classification (MLC) is presently the
most widely known and utilized (e.g. Curran and Hay (1986),
Yool et al. (1986)). MLC is often used as a standard classification
routine against which other classification algorithms are com
pared. This popularity is due to the fact that MLC is the optimal
classifier in the sense of minimizing Bayesian error. However,
MLC is a parametric classification method where the underlying
probability density function must be assumed a priori. We may
obtain a poor MLC performance if the true probability density
function is different from what is assumed in the model. In recent
years, researchers have attempted to provide non-parametric
classification methods to overcome this disadvantage of MLC,
and Layered Neural Networks (LNNs) have been proposed as
suitable for the efficient classification of remotely sensed images.
When using an LNN classifier, however, users have often been
faced with a generalization problem; generalization is concerned
with how well an LNN model performs with input on which the
model has not been previously trained. That is, an LNN classifier
usually performs well on a set of training data, but it may not
guarantee good generalization over all unknown data during the
actual classification process.
This paper discusses LNN classifier generalization, a controversi
al and often vague term in the neural network literature (Wan
(1990)), and clarifies its description. We introduce some tech
niques for generalization based on Akaike’s Information Criterion
and provide a feasible technique to design an LNN in considera
tion of its generalization capability. Finally, we apply the pro
posed technique to a practical land cover classification using
remotely sensed images, and demonstrate its potential.
2 BASIC FORMULATION OF THE LAYERED NEURAL
NETWORK CLASSIFIER
It has been proved that a three-layered neural network, when the
appropriate number of nodes are set in the hidden layer and the
sigmoidal activation function is used in the hidden and output
nodes, can approximate any continuous mapping (Gallant and
White (1988) and Funahashi (1989)). Therefore, in this study, we
only focus on three-layered neural networks, as shown in Figure
1.
Input Layer Hidden Layer Output Layer
Figure 1 Architecture of three-layered neural network.
PI-2-1

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