Advances in self-organizing maps and learning vector quantization: proceedings of the 10th International Workshop, WSOM 2014, Mittweida, Germany, July, 2-4, 2014
Gespeichert in:
| Weitere Verfasser: | |
|---|---|
| Format: | Elektronisch Tagungsbericht E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cham [u.a.]
Springer
2014
|
| Schriftenreihe: | Advances in intelligent systems and computing
295 |
| Schlagworte: | |
| Online-Zugang: | TUM01 Volltext Inhaltsverzeichnis Abstract |
| ISBN: | 9783319076959 9781322136820 |
| DOI: | 10.1007/978-3-319-07695-9 |
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| 245 | 1 | 0 | |a Advances in self-organizing maps and learning vector quantization |b proceedings of the 10th International Workshop, WSOM 2014, Mittweida, Germany, July, 2-4, 2014 |c Thomas Villmann ..., eds. |
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Datensatz im Suchindex
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| adam_text | ADVANCES IN SELF-ORGANIZING MAPS AND LEARNING VECTOR QUANTIZATION
/
: 2014
TABLE OF CONTENTS / INHALTSVERZEICHNIS
HOW MANY DISSIMILARITY/KERNEL SELF ORGANIZING MAP VARIANTS DO WE NEED
DYNAMIC FORMATION OF SELF-ORGANIZING MAPS
MS-SOM: MAGNITUDE SENSITIVE SELF-ORGANIZING MAPS.-BAGGED KERNEL SOM
PROBABILITY RIDGES AND DISTORTION FLOWS: VISUALIZING MULTIVARIATE TIME
SERIES USING A VARIATIONAL BAYESIAN MANIFOLD LEARNING METHOD
SHORT REVIEW OF DIMENSIONALITY REDUCTION METHODS BASED ON STOCHASTIC
NEIGHBOUR EMBEDDING
ATTENTION BASED CLASSIFICATION LEARNING IN GLVQ AND ASYMMETRIC
CLASSIFICATION ERROR ASSESSMENT.-VISUALIZATION AND CLASSIFICATION OF DNA
SEQUENCES USING PARETO LEARNING SELF ORGANIZING MAPS BASED ON FREQUENCY
AND CORRELATION COEFFICIENT
PROBABILISTIC PROTOTYPE CLASSIFICATION USING T-NORMS
REJECTION STRATEGIES FOR LEARNING VECTOR QUANTIZATION – A COMPARISON
OF PROBABILISTIC AND DETERMINISTIC APPROACHES
COMPARISON OF SPECTRUM CLUSTER ANALYSIS WITH PCA AND SPHERICAL SOM AND
RELATED ISSUES NOT AMENABLE TO PCA
EXPLOITING THE STRUCTURES OF THE U-MATRIX
PARTIAL MUTUAL INFORMATION FOR CLASSIFICATION ANALYSIS OF GENE
EXPRESSION DATA BY LEARNING VECTOR QUANTIZATION
COMPOSITION OF LEARNING PATTERNS USING SPHERICAL SELF-ORGANIZING MAPS IN
IMAGE ANALYSIS WITH SUBSPACE CLASSIFIER
SELF-ORGANIZING MAP FOR THE PRIZE-COLLECTING TRAVELING SALESMAN PROBLEM
A SURVEY OF SOM-BASED ACTIVE CONTOUR MODELS FOR IMAGE SEGMENTATION
BIOLOGICALLY PLAUSIBLE SOM REPRESENTATION OF THE ORTHOGRAPHIC FORM OF
50,000 FRENCH WORDS
PROTOTYPE-BASED CLASSIFIERS AND THEIR APPLICATION IN THE LIFE SCIENCES
GENERATIVE VERSUS DISCRIMINATIVE PROTOTYPE BASED CLASSIFICATION.-SOME
ROOM FOR GLVQ: SEMANTIC LABELING OF OCCUPANCY GRID MAPS
ANOMALY DETECTION BASED ON CONFIDENCE INTERVALS USING SOM WITH AN
APPLICATION TO HEALTH MONITORING
RFSOM - EXTENDING SELF-ORGANIZING FEATURE MAPS WITH ADAPTIVE METRICS TO
COMBINE SPATIAL AND TEXTURAL FEATURES FOR BODY POSE ESTIMATION
BEYOND STANDARD METRICS - ON THE SELECTION AND COMBINATION OF DISTANCE
METRICS FOR AN IMPROVED
CLASSIFICATION OF HYPERSPECTRAL DATA
THE SKY IS NOT THE LIMIT
DEVELOPMENT OF TARGET REACHING GESTURE MAP IN THE CORTEX AND ITS
RELATION TO THE MOTOR MAP: A SIMULATION STUDY
A CONCURRENT SOM-BASED CHAN-VESE MODEL FOR IMAGE SEGMENTATION
TEXT MINING OF LIFE-PHILOSOPHICL INSIGHTS
SOMBRERO: AN R PACKAGE FOR NUMERIC AND NON-NUMERIC SELF-ORGANIZING MAPS
K-NEAREST NEIGHBOR NONNEGATIVE MATRIX FACTORIZATION FOR LEARNING A
MIXTURE OF LOCAL SOM MODELS
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
ADVANCES IN SELF-ORGANIZING MAPS AND LEARNING VECTOR QUANTIZATION
/
: 2014
ABSTRACT / INHALTSTEXT
THE BOOK COLLECTS THE SCIENTIFIC CONTRIBUTIONS PRESENTED AT THE 10TH
WORKSHOP ON SELF-ORGANIZING MAPS (WSOM 2014) HELD AT THE UNIVERSITY OF
APPLIED SCIENCES MITTWEIDA, MITTWEIDA (GERMANY, SAXONY), ON JULY 2–4,
2014. STARTING WITH THE FIRST WSOM-WORKSHOP 1997 IN HELSINKI THIS
WORKSHOP FOCUSES ON NEWEST RESULTS IN THE FIELD OF SUPERVISED AND
UNSUPERVISED VECTOR QUANTIZATION LIKE SELF-ORGANIZING MAPS FOR DATA
MINING AND DATA CLASSIFICATION. THIS 10TH WSOM BROUGHT TOGETHER MORE
THAN 50 RESEARCHERS, EXPERTS AND PRACTITIONERS IN THE BEAUTIFUL SMALL
TOWN MITTWEIDA IN SAXONY (GERMANY) NEARBY THE MOUNTAINS ERZGEBIRGE TO
DISCUSS NEW DEVELOPMENTS IN THE FIELD OF UNSUPERVISED SELF-ORGANIZING
VECTOR QUANTIZATION SYSTEMS AND LEARNING VECTOR QUANTIZATION APPROACHES
FOR CLASSIFICATION. THE BOOK CONTAINS THE ACCEPTED PAPERS OF THE
WORKSHOP AFTER A CAREFUL REVIEW PROCESS AS WELL AS SUMMARIES OF THE
INVITED TALKS. AMONG THESE BOOK CHAPTERS THERE ARE EXCELLENT
EXAMPLES OF THE USE OF SELF-ORGANIZING MAPS IN AGRICULTURE, COMPUTER
SCIENCE, DATA VISUALIZATION, HEALTH SYSTEMS, ECONOMICS, ENGINEERING,
SOCIAL SCIENCES, TEXT AND IMAGE ANALYSIS, AND TIME SERIES ANALYSIS.
OTHER CHAPTERS PRESENT THE LATEST THEORETICAL WORK ON SELF-ORGANIZING
MAPS AS WELL AS LEARNING VECTOR QUANTIZATION METHODS, SUCH AS RELATING
THOSE METHODS TO CLASSICAL STATISTICAL DECISION METHODS. ALL THE
CONTRIBUTION DEMONSTRATE THAT VECTOR QUANTIZATION METHODS COVER A LARGE
RANGE OF APPLICATION AREAS INCLUDING DATA VISUALIZATION OF
HIGH-DIMENSIONAL COMPLEX DATA, ADVANCED DECISION MAKING AND
CLASSIFICATION OR DATA CLUSTERING AND DATA COMPRESSION
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
|
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| series | Advances in intelligent systems and computing |
| series2 | Advances in intelligent systems and computing |
| spellingShingle | Advances in self-organizing maps and learning vector quantization proceedings of the 10th International Workshop, WSOM 2014, Mittweida, Germany, July, 2-4, 2014 Advances in intelligent systems and computing Ingenieurwissenschaften Künstliche Intelligenz Artificial intelligence Engineering |
| title | Advances in self-organizing maps and learning vector quantization proceedings of the 10th International Workshop, WSOM 2014, Mittweida, Germany, July, 2-4, 2014 |
| title_auth | Advances in self-organizing maps and learning vector quantization proceedings of the 10th International Workshop, WSOM 2014, Mittweida, Germany, July, 2-4, 2014 |
| title_exact_search | Advances in self-organizing maps and learning vector quantization proceedings of the 10th International Workshop, WSOM 2014, Mittweida, Germany, July, 2-4, 2014 |
| title_full | Advances in self-organizing maps and learning vector quantization proceedings of the 10th International Workshop, WSOM 2014, Mittweida, Germany, July, 2-4, 2014 Thomas Villmann ..., eds. |
| title_fullStr | Advances in self-organizing maps and learning vector quantization proceedings of the 10th International Workshop, WSOM 2014, Mittweida, Germany, July, 2-4, 2014 Thomas Villmann ..., eds. |
| title_full_unstemmed | Advances in self-organizing maps and learning vector quantization proceedings of the 10th International Workshop, WSOM 2014, Mittweida, Germany, July, 2-4, 2014 Thomas Villmann ..., eds. |
| title_short | Advances in self-organizing maps and learning vector quantization |
| title_sort | advances in self organizing maps and learning vector quantization proceedings of the 10th international workshop wsom 2014 mittweida germany july 2 4 2014 |
| title_sub | proceedings of the 10th International Workshop, WSOM 2014, Mittweida, Germany, July, 2-4, 2014 |
| topic | Ingenieurwissenschaften Künstliche Intelligenz Artificial intelligence Engineering |
| topic_facet | Ingenieurwissenschaften Künstliche Intelligenz Artificial intelligence Engineering |
| url | https://doi.org/10.1007/978-3-319-07695-9 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027472259&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027472259&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV040889154 |
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