Open Access. Powered by Scholars. Published by Universities.®
- Discipline
- Publication
- Publication Type
Articles 1 - 4 of 4
Full-Text Articles in Computer Sciences
Per-Pixel Cloud Cover Classification Of Multispectral Landsat-8 Data, Salome E. Carrasco [*], Torrey J. Wagner, Brent T. Langhals
Per-Pixel Cloud Cover Classification Of Multispectral Landsat-8 Data, Salome E. Carrasco [*], Torrey J. Wagner, Brent T. Langhals
Faculty Publications
Random forest and neural network algorithms are applied to identify cloud cover using 10 of the wavelength bands available in Landsat 8 imagery. The methods classify each pixel into 4 different classes: clear, cloud shadow, light cloud, or cloud. The first method is based on a fully connected neural network with ten input neurons, two hidden layers of 8 and 10 neurons respectively, and a single-neuron output for each class. This type of model is considered with and without L2 regularization applied to the kernel weighting. The final model type is a random forest classifier created from an ensemble of …
The Effectiveness Of Using Diversity To Select Multiple Classifier Systems With Varying Classification Thresholds, Harris K. Butler Iv, Mark A. Friend, Kenneth W. Bauer, Trevor J. Bihl
The Effectiveness Of Using Diversity To Select Multiple Classifier Systems With Varying Classification Thresholds, Harris K. Butler Iv, Mark A. Friend, Kenneth W. Bauer, Trevor J. Bihl
Faculty Publications
In classification applications, the goal of fusion techniques is to exploit complementary approaches and merge the information provided by these methods to provide a solution superior than any single method. Associated with choosing a methodology to fuse pattern recognition algorithms is the choice of algorithm or algorithms to fuse. Historically, classifier ensemble accuracy has been used to select which pattern recognition algorithms are included in a multiple classifier system. More recently, research has focused on creating and evaluating diversity metrics to more effectively select ensemble members. Using a wide range of classification data sets, methodologies, and fusion techniques, current diversity …
Text Classification Of Installation Support Contract Topic Models For Category Management, William C. Sevier
Text Classification Of Installation Support Contract Topic Models For Category Management, William C. Sevier
Theses and Dissertations
Air Force Installation Contracting Agency manages nearly 18 percent of total Air Force spend, equating to approximately 57 billion dollars. To improve strategic sourcing, the organization is beginning to categorize installation-support spend and assign accountable portfolio managers to respective spend categories. A critical task in this new strategic environment includes the appropriate categorization of Air Force contracts into newly created, manageable spend categories. It has been recognized that current composite categories have the opportunity to be further distinguished into sub-categories leveraging text analytics on the contract descriptions. Furthermore, upon establishing newly constructed categories, future contracts must be classified into these …
Radial Complexity Estimation For Improved Generalization In Artificial Neural Networks, Lemuel R. Myers Jr.
Radial Complexity Estimation For Improved Generalization In Artificial Neural Networks, Lemuel R. Myers Jr.
Theses and Dissertations
When training an artificial neural network (ANN) for classification using backpropagation of error, the weights are usually updated by minimizing the sum-squared error on the training set. As training ensues, overtraining may be observed as the network begins to memorize the training data. This occurs because, as the magnitude of the weight vector, W, grows, the decision boundaries become overly complex in much the same way as a too-high order polynomial approximation can overfit a data set in a regression problem. Since w grows during standard backpropagation, it is important to initialize the weights with consideration to the importance of …