scholarly journals THE USE OF NEURAL NETWORKS IN RARE VEGETATION COMMUNITIES CLASSIFICATION

2014 ◽  
pp. 171-184
Author(s):  
E. M. Gambarova
Keyword(s):  
Multilayer Perceptron ◽  
Classification Scheme ◽  
High Spatial Resolution ◽  
Statistical Tests ◽  
Classification Schemes ◽  
Geoinformation Technologies ◽  
Training Samples ◽  
Community Types ◽  
Neural Classifier ◽  
Initial Classification

This paper describes training of Multilayer Perceptron Neural classifier to extract rare vegetation objects from high spatial resolution IKONOS satellite imagery. There have been considered three options of training of the Multilayer Perceptron Neural according to three different classification schemes. At first 12 type of rare vegetation community types were defined, a main classification scheme (“Initial classification scheme”) was designed on that base. After prelim statistical tests on training samples two modification algorithms of the classification scheme were defined: the first one led to creating of scheme consisting of 7 classes (“Modified classification scheme”) and second one led us to creating of 5-classes scheme (“Optimized classification scheme“). The learning procedures of these classifiers are described as well as analysis and post processing of extraction results of objects of interest using Geoinformation Technologies in details.

Reclassification at Chelsea College of Art & Design Library

2011 ◽  
Vol 36 (4) ◽  
pp. 34-40
Author(s):  
Elizabeth Lawes ◽  
Tania Olsson
Keyword(s):  
Art Education ◽  
Public Art ◽  
Art History ◽  
Classification Scheme ◽  
Fine Art ◽  
Classification Schemes ◽  
Spatial Design ◽  
Art Design ◽  
Large Sections ◽  
Initial Classification

This article examines some of the problems associated with the initial classification and subsequent reclassification of a specialist Fine Art library. The Library at the then Chelsea School of Art was established in the early 1960s. It was unusual, ‘being predominantly a fine art (painting and sculpture) institution, with lesser responsibilities in design.’ Most ‘off the peg’ classification schemes do not incorporate enough flexibility for the detail required by such a specific collection, but do include large sections devoted to design subjects which were unnecessary at the time. It was decided, therefore, to create a bespoke scheme for the Chelsea collection, and this was adapted several times over the years to fit in with the changing landscape of art history and art education. In January 2005, Chelsea College of Art & Design relocated to a new unified site on Millbank, merging the three very specialised libraries: Manresa Road (Fine Art), Hugon Road (Interior and Spatial Design, Graphics and Illustration) and Lime Grove (Textiles and Public Art). One of the major challenges of this relocation was to bring all the collections together under one classification scheme.

scholarly journals Declassifying Myrmecophily in the Coleoptera to Promote the Study of Ant-Beetle Symbioses

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Glené Mynhardt
Keyword(s):  
Classification Scheme ◽  
Morphological Characteristics ◽  
Behavioral Data ◽  
Target Species ◽  
Classification Schemes ◽  
Future Studies ◽  
Symbiotic Associations ◽  
Behavioral Studies ◽  
Morphological Adaptations ◽  
Evolutionary Studies

The symbiotic associations between beetles and ants have been observed in at least 35 beetle families. Among myrmecophiles, beetles exhibit the most diverse behavioral and morphological adaptations to a life with ants. These various associations have historically been grouped into discrete but overlapping behavioral categories, many of which are still used in the modern literature. While these behavioral classifications provide a rich foundation for the study of ant-beetle symbioses, the application of these systems in future studies may be less than effective. Since morphological characteristics often provide the only information of myrmecophilous beetles, they should be studied in a species-by-species fashion, as behavioral data are often limited or unavailable. Similarly, behavioral studies should focus on the target species at hand, avoiding discrete classification schemes. I formally propose the rejection of any classification scheme, in order to promote future studies of myrmecophily in both taxonomic and evolutionary studies.

scholarly journals Geo-Object-Based Land Cover Map Update for High-Spatial-Resolution Remote Sensing Images via Change Detection and Label Transfer

2020 ◽  
Vol 12 (1) ◽  
pp. 174
Author(s):  
Tianjun Wu ◽  
Jiancheng Luo ◽  
Ya’nan Zhou ◽  
Changpeng Wang ◽  
Jiangbo Xi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Change Detection ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Data Set ◽  
Label Transfer ◽  
Object Based ◽  
Training Samples ◽  
Map Updating

Land cover (LC) information plays an important role in different geoscience applications such as land resources and ecological environment monitoring. Enhancing the automation degree of LC classification and updating at a fine scale by remote sensing has become a key problem, as the capability of remote sensing data acquisition is constantly being improved in terms of spatial and temporal resolution. However, the present methods of generating LC information are relatively inefficient, in terms of manually selecting training samples among multitemporal observations, which is becoming the bottleneck of application-oriented LC mapping. Thus, the objectives of this study are to speed up the efficiency of LC information acquisition and update. This study proposes a rapid LC map updating approach at a geo-object scale for high-spatial-resolution (HSR) remote sensing. The challenge is to develop methodologies for quickly sampling. Hence, the core step of our proposed methodology is an automatic method of collecting samples from historical LC maps through combining change detection and label transfer. A data set with Chinese Gaofen-2 (GF-2) HSR satellite images is utilized to evaluate the effectiveness of our method for multitemporal updating of LC maps. Prior labels in a historical LC map are certified to be effective in a LC updating task, which contributes to improve the effectiveness of the LC map update by automatically generating a number of training samples for supervised classification. The experimental outcomes demonstrate that the proposed method enhances the automation degree of LC map updating and allows for geo-object-based up-to-date LC mapping with high accuracy. The results indicate that the proposed method boosts the ability of automatic update of LC map, and greatly reduces the complexity of visual sample acquisition. Furthermore, the accuracy of LC type and the fineness of polygon boundaries in the updated LC maps effectively reflect the characteristics of geo-object changes on the ground surface, which makes the proposed method suitable for many applications requiring refined LC maps.

scholarly journals Automatic Changes Detection between Outdated Building Maps and New VHR Images Based on Pre-Trained Fully Convolutional Feature Maps

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5538
Author(s):  
Yunsheng Zhang ◽  
Yaochen Zhu ◽  
Haifeng Li ◽  
Siyang Chen ◽  
Jian Peng ◽  
...  
Keyword(s):  
Cross Validation ◽  
High Spatial Resolution ◽  
Data Cleaning ◽  
Poor Performance ◽  
Uncertainty Estimation ◽  
Feature Maps ◽  
Existing Building ◽  
Feature Extractor ◽  
Changes Detection ◽  
Initial Classification

Detecting changes between the existing building basemaps and newly acquired high spatial resolution remotely sensed (HRS) images is a time-consuming task. This is mainly because of the data labeling and poor performance of hand-crafted features. In this paper, for efficient feature extraction, we propose a fully convolutional feature extractor that is reconstructed from the deep convolutional neural network (DCNN) and pre-trained on the Pascal VOC dataset. Our proposed method extract pixel-wise features, and choose salient features based on a random forest (RF) algorithm using the existing basemaps. A data cleaning method through cross-validation and label-uncertainty estimation is also proposed to select potential correct labels and use them for training an RF classifier to extract the building from new HRS images. The pixel-wise initial classification results are refined based on a superpixel-based graph cuts algorithm and compared to the existing building basemaps to obtain the change map. Experiments with two simulated and three real datasets confirm the effectiveness of our proposed method and indicate high accuracy and low false alarm rate.

scholarly journals Long-Duration Solar and Stellar Flares

1989 ◽  
Vol 104 (1) ◽  
pp. 313-322
Author(s):  
Giannina Poletto
Keyword(s):  
Solar Flares ◽  
Classification Scheme ◽  
High Spatial Resolution ◽  
Physical Parameters ◽  
Additional Information ◽  
Stellar Flares ◽  
Long Duration ◽  
Model Predictions ◽  
Flare Region ◽  
Reconnection Model

AbstractAccording to one of the most popular classifications, solar flares may be assigned either to the category of small short-lived events, or to the category of large, long-duration two-ribbon (2-R) flares. Even if such a broad division oversimplifies the flare phenomenon, our knowledge of the characteristics of stellar flares is so poor, that it is worthwhile to investigate the possibility of adopting this classification scheme for stellar flares as well. In particular we will analyze Einstein observations of a long duration flare on EQ Peg to establish whether it might be considered as a stellar analogy of 2-R solar events. To this end we apply to EQ Peg data a reconnection model, developed originally for solar 2-R flares, and conclude that stellar observations are consistent with model predictions, although additional information is required to identify uniquely the physical parameters of the flare region. Application of the model to integrated observations of a 2-R solar flare, for which high spatial resolution data are also available, shows, however, that future integrated observations may allow us to solve the ambiguities of the model and use it as a diagnostic tool for a better understanding of stellar flares.

Classification of montane forest community types in the Cedar River drainage of western Washington, U.S.A.

1977 ◽  
Vol 7 (2) ◽  
pp. 217-225 ◽  
Author(s):  
Roger Del Moral ◽  
James N. Long
Keyword(s):  
Discriminant Analysis ◽  
Large Scale ◽  
Classification Scheme ◽  
Forest Community ◽  
Vegetation Types ◽  
Agglomerative Clustering ◽  
Lower Elevation ◽  
Community Types ◽  
Western Washington

Vegetation of the Cedar River watershed, located in the Cascade Mountains of western Washington, was analyzed by an agglomerative clustering method followed by discriminant analysis. Stepwise mutliple discriminant analysis provided a means to reallocate stands and assists in the production of a classification scheme and a key to the vegetation types. Ten types are recognized, six from upper-elevation older-growth stands, and four seral types from lower elevation stands logged since 1900. Each type can be identified in the field with a simple key based on cover percentage. The key provides a means for large-scale vegetation mapping with a limited amount of effort.

Classification schemes in art libraries in the United Kingdom

2002 ◽  
Vol 27 (1) ◽  
pp. 18-22 ◽  
Author(s):  
Sarah Currier
Keyword(s):  
Classification Scheme ◽  
Controlled Vocabulary ◽  
Electronic Resource ◽  
Classification Schemes ◽  
The United Kingdom ◽  
Discussion List ◽  
The One ◽  
The Uk ◽  
E Mail ◽  
Decimal Classification

Subject access to physical or electronic resource collections can be divided into two complementary areas: searching and browsing. Searching involves the use of subject headings, indexing terms from a controlled vocabulary, or natural language keywords. Browsing, whether along a shelf or through a subject tree on the Web, requires the application of some kind of taxonomy or classification scheme. This article looks at what class schemes art libraries are using to arrange their book collections in the UK today. Based on an informal survey via the ARLIS e-mail discussion list, it appears that the Dewey Decimal Classification is not only the most commonly used class scheme, but the one most art libraries choose when they reclassify their library.

scholarly journals Revised nomenclature and SNP barcode for Mycobacterium tuberculosis lineage 2

2021 ◽  
Vol 7 (11) ◽  
Author(s):  
Yuttapong Thawornwattana ◽  
Surakameth Mahasirimongkol ◽  
Hideki Yanai ◽  
Htet Myat Win Maung ◽  
Zhezhe Cui ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Type Species ◽  
Classification Scheme ◽  
Snp Markers ◽  
Drug Resistant ◽  
Fine Scale ◽  
Content Type ◽  
Classification Schemes ◽  
Disease Epidemiology ◽  
Lineage 2

Mycobacterium tuberculosis (Mtb) lineage 2 (L2) strains are present globally, contributing to a widespread tuberculosis (TB) burden, particularly in Asia where both prevalence of TB and numbers of drug resistant TB are highest. The increasing availability of whole-genome sequencing (WGS) data worldwide provides an opportunity to improve our understanding of the global genetic diversity of Mtb L2 and its association with the disease epidemiology and pathogenesis. However, existing L2 sublineage classification schemes leave >20 % of the Modern Beijing isolates unclassified. Here, we present a revised SNP-based classification scheme of L2 in a genomic framework based on phylogenetic analysis of >4000 L2 isolates from 34 countries in Asia, Eastern Europe, Oceania and Africa. Our scheme consists of over 30 genotypes, many of which have not been described before. In particular, we propose six main genotypes of Modern Beijing strains, denoted L2.2.M1–L2.2.M6. We also provide SNP markers for genotyping L2 strains from WGS data. This fine-scale genotyping scheme, which can classify >98 % of the studied isolates, serves as a basis for more effective monitoring and reporting of transmission and outbreaks, as well as improving genotype-phenotype associations such as disease severity and drug resistance. This article contains data hosted by Microreact.

Modeling a Classification Scheme of Epileptic Seizures Using Ontology Web Language

2012 ◽  
pp. 44-59
Author(s):  
Bhaswati Ghosh ◽  
Partha S. Ghosh ◽  
Iftikhar U. Sikder
Keyword(s):  
Classification Scheme ◽  
Epileptic Seizures ◽  
Disease Classification ◽  
Rule Engine ◽  
Classification Schemes ◽  
Neurological Condition ◽  
New Knowledge ◽  
Java Platform ◽  
Complex Knowledge

Ontology-based disease classification offers a way to rigorously assign disease types and to reuse diagnostic knowledge. However, ontology itself is not sufficient for fully representing the complex knowledge needed in classification schemes which are continuously evolving. This article describes the application of SWRL/OWL-DL to the representation of knowledge intended for proper classification of a complex neurological condition, namely epilepsy. The authors present a rigorous and expandable approach to the ontological classification of epileptic seizures based on the 1981ILAE classification. It provides a classification knowledge base that can be extended with rules that describe constraints in SWRL. Moreover, by transforming an OWL classification scheme into JESS (rule engine in Java platform) facts and by transforming SWRL constraints into JESS, logical inferences and reasoning provide a mechanism to discover new knowledge and facts. The logic representation of epileptic classification amounts to greater community understanding among practitioners, knowledge reuse and interoperability.

Electronic games classification in the library of congress and Dewey classification schemes: a comparative study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nahed Salem ◽  
Ahmed Maher Khafaga Shehata
Keyword(s):  
Design Methodology ◽  
Classification Scheme ◽  
Library Of Congress ◽  
Content Type ◽  
Classification Schemes ◽  
The Subject ◽  
The Difference ◽  
Electronic Games ◽  
Decimal Classification

Purpose The study aims to explore the classification of electronic games in Dewey decimal classification (DDC) and The Library of Congress classification (LCC) schemes. Design/methodology/approach The study adopted a comparative analytical method to explore the topic in both the DDC and the LCC schemes by comparing its processing method in both schemes. The study measures the extent to which both schemes succeed in allocating notations covering the topic’s literature. Findings The study reached several results, the most important of which are: the difference between the two main cognitive sections, to which they belong to the topic, namely, arts and recreation (700) in the DDC scheme and the geography section (G) in the LCC scheme, while they were found to share the same sub-section scheme. The two schemes do not allocate notations to address the subject of electronic games as literature and other notations that have not been embodied for electronic games themselves or in the form of a compact disc or other media. Originality/value As far as we know, this is the first paper that compares the treatment of video games in DDC and Library of Congress classification schemes. The study allows for understanding the difference in the treatment of topics in both schemes, which would help in the decision of the adoption of a particular classification scheme.

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