搜索结果: 1-15 共查到“工学 UNSUPERVISED”相关记录34条 . 查询时间(0.087 秒)
Labeling data can be a chore. It’s the main source of sustenance for computer-vision models; without it, they’d have a lot of difficulty identifying objects, people, and other important image characte...
MODEL FOR LAND COVER ESTIMATION USING UNSUPERVISED MACHINE LEARNING ON GOOGLE MAPS COLOR IMAGES
Unsupervised learning algorithms CORINE nomenclature Google Static Maps API k-means clustering
2019/2/27
Remote sensing data and satellite images are broadly used for land cover information. There are so many challenges to classify pixels on the basis of features and characteristics. Generally it is pixe...
NOVEL HYPERSPECTRAL ANOMALY DETECTION METHODS BASED ON UNSUPERVISED NEAREST REGULARIZED SUBSPACE
Anomaly detection Hyperspectral imagery Unsupervised nearest regularized subspace Outlier Removal Local summation Dual-window sliding
2018/5/14
Anomaly detection has been of great interest in hyperspectral imagery analysis. Most conventional anomaly detectors merely take advantage of spectral and spatial information within neighboring pixels....
AN UNSUPERVISED CHANGE DETECTION BASED ON TEST STATISTIC AND KI FROM MULTI-TEMPORAL AND FULL POLARIMETRIC SAR IMAGES
Change Detection Multi-temporal Synthetic Aperture Radar (SAR) Test Statistic Kittler and Illingworth (KI)
2016/11/23
Accurate and timely change detection of Earth’s surface features is extremely important for understanding relationships and interactions between people and natural phenomena. Many traditional methods ...
UNSUPERVISED WISHART CLASSFICATION OF WETLANDS IN NEWFOUNDLAND,CANADA USING POLSAR DATA BASED ON FISHER LINEAR DISCRIMINANT ANALYSIS
Polarimetric Synthetic Aperture Radar (PolSAR) Unsupervised Wishart Classification Fisher Linear Discrimination Feature Weighting
2016/11/23
Polarimetric Synthetic Aperture Radar (PolSAR) imagery is a complex multi-dimensional dataset, which is an important source of information for various natural resources and environmental classificatio...
KERNEL FEATURE CROSS-CORRELATION FOR UNSUPERVISED QUANTIFICATION OF DAMAGE FROM WINDTHROW IN FORESTS
Feature matching Kernel normalized cross-correlation Forest Support Vector Machines
2016/11/23
In this study estimation of tree damage from a windthrow event using feature detection on RGB high resolution imagery is assessed. An accurate quantitative assessment of the damage in terms of volume ...
UNSUPERVISED CLASSIFICATION OF POLARIMETRIC SAR DATA USING IMAGE CLUSTERING AND H/A/α DECOMPOSITION
Image Classification Data Clustering H/A/a Polarimetric SAR Iteration POLSARPRO
2016/3/17
This paper proposed a method of unsupervised classification of polarimetric SAR data based on image clustering and H/A/a decomposition. Fully polarimetric L band data collected by ALOS PALSAR system w...
DECISION FUSION FOR THE UNSUPERVISED CHANGE DETECTION OF MULTITEMPORAL SAR
SAR Unsupervised change detection Information fusion Fuzzy sets theory
2016/1/3
The unsupervised change detection of multitemporal SAR usually can get different results through different threshold selection algorithms. It is hard to determine what kinds of results are the best. I...
UNSUPERVISED INFORMATION EXTRACTION USING ABSORPTION LINE IN HYPERION IMAGES
Hyperspectral Imaging Absorption Bands Clustering Derivative Analysis
2015/12/31
Using recently developed techniques, a significant amount of Information could be extracted from spectral signatures of surface material in their continuous spectra. One of the main applications in wh...
UNSUPERVISED CHANGE DETECTION IN SAR IMAGES USING GAUSSIAN MIXTURE MODELS
Gaussian Mixture model Change Detection SAR images Difference image Multi-temporal Images
2016/1/15
In this paper, we propose a method for unsupervised change detection in Remote Sensing Synthetic Aperture Radar (SAR) images. This method is based on the mixture modelling of the histogram of differen...
The task of event coreference resolution plays a critical role in many natural language processing applications such as information extraction, question answering, and topic detection
and tracking. I...
GENETIC ALGORITHMS FOR THE UNSUPERVISED CLASSIFICATION OF SATELLITE IMAGES
Remote Sensing Analysis Unsupervised Classification Genetic Algorithm Davies-Bouldin's Index Heuristic Algorithm ISODATA
2015/8/31
Traditionally, an unsupervised classification divides all pixels within an image into a corresponding class pixel by pixel; the number of clusters usually needs to be fixed a priori by a human analyst...
GENETIC ALGORITHMS FOR THE UNSUPERVISED CLASSIFICATION OF SATELLITE IMAGES
Remote Sensing Analysis Unsupervised Classification Genetic Algorithm Davies-Bouldin's Index Heuristic Algorithm ISODATA
2015/8/28
Traditionally, an unsupervised classification divides all pixels within an image into a corresponding class pixel by pixel; the number of clusters usually needs to be fixed a priori by a human analyst...
Unsupervised image endmemeber definition in multisensor image data
Imaging spectroscopy Endmember selection Urban monitoring
2015/8/21
In a recent studie (Greiwe and Ehlers, 2005), the author developed a decision based data fusion approach for the analysis of spatial
and spectral high resolution image data of an urban scene. Image s...
EFFECTS OF UNSUPERVISED FULLY CONSTRAINED LEAST SQUARES LINEAR SPECTRAL MIXTURE ANALYSIS METHOD ON AUTOMATIC CLASSIFICATION OF TM IMAGE
classification of remote sensing image linear spectral mixture mode
2015/7/30
Statistical analysis is a widely used traditional technique for classification and discrimination in remotely sensed images, which
supposes that there is only one endmember in an image pixel. Howeve...