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Full-Text Articles in Computer Sciences
Mind The Gap: Situated Spatial Language A Case-Study In Connecting Perception And Language, John D. Kelleher
Mind The Gap: Situated Spatial Language A Case-Study In Connecting Perception And Language, John D. Kelleher
Other
This abstract reviews the literature on computational models of spatial semantics and the potential of deep learning models as an useful approach to this challenge.
Improving Swarm Performance By Applying Machine Learning To A New Dynamic Survey, John Taylor Jackson
Improving Swarm Performance By Applying Machine Learning To A New Dynamic Survey, John Taylor Jackson
Master's Theses
A company, Unanimous AI, has created a software platform that allows individuals to come together as a group or a human swarm to make decisions. These human swarms amplify the decision-making capabilities of both the individuals and the group. One way Unanimous AI increases the swarm’s collective decision-making capabilities is by limiting the swarm to more informed individuals on the given topic. The previous way Unanimous AI selected users to enter the swarm was improved upon by a new methodology that is detailed in this study. This new methodology implements a new type of survey that collects data that is …
Multimodal Depression Detection: An Investigation Of Features And Fusion Techniques For Automated Systems, Michelle Renee Morales
Multimodal Depression Detection: An Investigation Of Features And Fusion Techniques For Automated Systems, Michelle Renee Morales
Dissertations, Theses, and Capstone Projects
Depression is a serious illness that affects a large portion of the world’s population. Given the large effect it has on society, it is evident that depression is a serious health issue. This thesis evaluates, at length, how technology may aid in assessing depression. We present an in-depth investigation of features and fusion techniques for depression detection systems. We also present OpenMM: a novel tool for multimodal feature extraction. Lastly, we present novel techniques for multimodal fusion. The contributions of this work add considerably to our knowledge of depression detection systems and have the potential to improve future systems by …
Using Autoencoder To Reduce The Length Of The Autism Diagnostic Observation Schedule (Ados), Sara Hussain Daghustani
Using Autoencoder To Reduce The Length Of The Autism Diagnostic Observation Schedule (Ados), Sara Hussain Daghustani
Electronic Theses, Projects, and Dissertations
This thesis uses autoencoders to explore the possibility of reducing the length of the Autism Diagnostic Observation Schedule (ADOS), which is a series of tests and observations used to diagnose autism spectrum disorders in children, adolescents, and adults of different developmental levels. The length of the ADOS, directly and indirectly, causes barriers to its access for many individuals, which means that individuals who need testing are unable to get it. Reducing the length of the ADOS without significantly sacrificing its accuracy would increase its accessibility. The autoencoders used in this thesis have specific connections between layers that mimic the sectional …