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Now showing items 31-37 of 37
Classification of LiDar Data Using Window-Based Techniques
(North Dakota State University, 2016)
Given LiDAR maps, we focus on identifying anthropologically relevant ditches automatically on the map. Archeologists can identify these features visually at the site, but approaches based on remotely sensed data would be ...
Effect of Prompting Techniques and Learning Styles on Requirements Elicitation
(North Dakota State University, 2016)
Research efforts on improving requirements elicitation are focused on developing and validating better techniques for eliciting a comprehensive set of requirements. However, there isn't enough empirical evidence available ...
Using Learning Styles of Software Professionals to Improve Their Inspection Performance: An Empirical Study
(North Dakota State University, 2016)
In the IT industry, good requirements specification plays a vital role in software projects success. Researches revealed that early detection of faults in a requirements document saves significant amount of rework. To ...
Sentiment Analysis and Opinion Mining on Twitter with GMO Keyword
(North Dakota State University, 2016)
Twitter are a new source of information for data mining techniques. Messages posted through Twitter provide a major information source to gauge public sentiment on topics ranging from politics to fashion trends. The purpose ...
Recommendation of Business Intelligence Tool
(North Dakota State University, 2016)
Business Intelligence (BI) is extremely vital for organizations for delivering useful information from the large volumes of data being collected. There are many BI tools available but no single tool is appropriate for every ...
Software Metrics Tool
(North Dakota State University, 2016)
A software metric is the measurement of a particular characteristic of a software program. These metrics are very useful for optimizing the performance of the software, managing resources, debugging, schedule planning, ...
Object Classification Using Stacked Autoencoder and Convolutional Neural Network
(North Dakota State University, 2016)
In the recent years, deep learning has shown to have a formidable impact on object classification and has bolstered the advances in machine learning research. Many image datasets such as MNIST, CIFAR-10, SVHN, Imagenet, ...