Add to ORKGA method is presented for feature extraction of multispectral scanner data. Non-training data is used to demonstrate the reduction in processing time that can be obtained by using feature extraction rather than feature selection
Efficient acquisition and utilization of remotely sensed data requires an extensive a priori evaluat...
The standard procedure at LARS for classification analysis of aircraft scanner data has been to trai...
Feature selection software was developed at the Earth Resources Laboratory that is capable of inputt...
A method is presented for feature extraction of multispectral scanner data. Non-training data is use...
Research in multispectral data processing at LARS/Purdue is directed at supporting a substantial lev...
The applicability of recognition-processing procedures for multispectral scanner data from areas and...
The possibility of approaching multispectral data without any assumption on its statistical nature i...
The advantages and disadvantages of various remote sensing instrumentation and analysis techniques a...
An important step in the use of pattern recognition methods is the training of the classifier. This ...
A method of classification of digitized multispectral image data is described. It is designed to exp...
Two parallel and overlapping approaches to classification of remotely sensed data with the aid of sp...
A new technique, which greatly facilitates the computer analysis of large-area multi-feature imagery...
Adaptive data processing procedures are applied to the problem of classifying objects in a scene sca...
A two-step classification algorithm for processing multispectral scanner data has been developed and...
The multispectral techniques have shown themselves capable of solving problems in a large number of ...
Efficient acquisition and utilization of remotely sensed data requires an extensive a priori evaluat...
The standard procedure at LARS for classification analysis of aircraft scanner data has been to trai...
Feature selection software was developed at the Earth Resources Laboratory that is capable of inputt...
A method is presented for feature extraction of multispectral scanner data. Non-training data is use...
Research in multispectral data processing at LARS/Purdue is directed at supporting a substantial lev...
The applicability of recognition-processing procedures for multispectral scanner data from areas and...
The possibility of approaching multispectral data without any assumption on its statistical nature i...
The advantages and disadvantages of various remote sensing instrumentation and analysis techniques a...
An important step in the use of pattern recognition methods is the training of the classifier. This ...
A method of classification of digitized multispectral image data is described. It is designed to exp...
Two parallel and overlapping approaches to classification of remotely sensed data with the aid of sp...
A new technique, which greatly facilitates the computer analysis of large-area multi-feature imagery...
Adaptive data processing procedures are applied to the problem of classifying objects in a scene sca...
A two-step classification algorithm for processing multispectral scanner data has been developed and...
The multispectral techniques have shown themselves capable of solving problems in a large number of ...
Efficient acquisition and utilization of remotely sensed data requires an extensive a priori evaluat...
The standard procedure at LARS for classification analysis of aircraft scanner data has been to trai...
Feature selection software was developed at the Earth Resources Laboratory that is capable of inputt...