Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Physical Sciences and Mathematics
Information Retrieval-Based Optimization Approaches For Requirement Traceability Recovery, Danissa Victoria Rodriguez Caraballo
Information Retrieval-Based Optimization Approaches For Requirement Traceability Recovery, Danissa Victoria Rodriguez Caraballo
LSU Doctoral Dissertations
Requirements traceability provides support for important software engineering activities. Requirements traceability recovery (RTR) is becoming increasingly important due to the numerous benefits to the overall quality of software. Improving the RTR problem has become an active topic of research for software engineers; researchers have proposed a number of approaches for improving and automating RTR across the requirements and the source code of the system. Textual analysis and Information Retrieval (IR) techniques have been applied to the RTR problem for many years; however, most of the existing IR-based methodologies applied to the RTR problem are semiautomatic or time-consuming, even though many …
A Study On Large-Scale Deep Learning In Bioinformatics And Biomedical Applications, Shayan Shams
A Study On Large-Scale Deep Learning In Bioinformatics And Biomedical Applications, Shayan Shams
LSU Doctoral Dissertations
Recent advances in Artificial Intelligence and deep learning have provided researchers in various fields insights into the analysis of multiple datasets. These applications include image analysis, text analysis, and many more. However, the effectiveness of deep learning in some areas, such as biomedical imaging and genomic research, has been overshadowed by the variance in the types and complexity of data. This is in addition to the expensive labeling process and the limited size of datasets in these fields. These challenges require advanced deep learning models capable of learning from a small dataset and also from a small number of labeled …