7 citations · 9 across the 4 of their papers we have counts for
5 papers
Video Contents Understanding using Deep Neural Networks
Mohammadhossein Toutiaee, Abbas Keshavarzi, Abolfazl Farahani +1
We propose a novel application of Transfer Learning to classify video-frame sequences over multiple classes. This is a pre-weighted model that does not require to train a fresh CNN…
GELATO and SAGE: An Integrated Framework for MS Annotation
Khalifeh AlJadda, Rene Ranzinger, Melody Porterfield +6
Several algorithms and tools have been developed to (semi) automate the process of glycan identification by interpreting Mass Spectrometric data. However, each has limitations when…
Mining Massive Hierarchical Data Using a Scalable Probabilistic Graphical Model
Khalifeh AlJadda, Mohammed Korayem, Camilo Ortiz +7
Probabilistic Graphical Models (PGM) are very useful in the fields of machine learning and data mining. The crucial limitation of those models,however, is the scalability. The Baye…
PGMHD: A Scalable Probabilistic Graphical Model for Massive Hierarchical Data Problems
Khalifeh AlJadda, Mohammed Korayem, Camilo Ortiz +3
In the big data era, scalability has become a crucial requirement for any useful computational model. Probabilistic graphical models are very useful for mining and discovering data…
Unicode in Domain-Specific Programming Languages for Modeling & Simulation: ScalaTion as a Case Study
Michael E. Cotterell, John A. Miller, Tom Horton
As recent programming languages provide improved conciseness and flexibility of syntax, the development of embedded or internal Domain-Specific Languages has increased. The field o…