Search results | J. Murrey Atkins Library

Title: Aviatar- An Augmented Reality System to Improve Pilot Performance for Unmanned Aerial Systems
Author: Abbott, Robert
Date Created: 2021
Description: In the modern airspace, small unmanned aircraft systems (UAS) such as drones are becoming increasingly popular with both amateur enthusiasts as well as professional pilots. In the three years following the initiation of the small drone registratio...

Title: Aviatar- An Augmented Reality System to Improve Pilot Performance for Unmanned Aerial Systems
Author: Abbott, Robert
Date Created: 2021
Subjects--Topical: Computer science, Aerospace engineering, Cognitive psychology
Description: In the modern airspace, small unmanned aircraft systems (UAS) such as drones are becoming increasingly popular with both amateur enthusiasts as well as professional pilots. In the three years following the initiation of the small drone registratio...

Title: Better modeling of matching possibilities and uncertainty for offline visual multiple object tracking
Author: Rice, Lance
Date Created: 2021
Subjects--Topical: Computer science
Description: The task of visually tracking multiple objects remains an active field of algorithm development even after several decades of research in the computer vision community. One reason it remains an active research area is that identifying and maintain...

Title: Deep Learning-based Digital Human Modeling and Applications
Author: Ali, Ayman
Date Created: 2023
Subjects--Topical: Artificial intelligence, Biomechanics, Computer science
Description: Recent advancements in the domain of deep learning models have engendered remarkable progress across numerous computer vision tasks. Notably, there has been a burgeoning interest in the field of recovering three-dimensional (3D) human models from ...

Title: Detecting Discrete Emotions in Text Using Neural Networks
Author: Seyeditabari, Seyed Armin
Date Created: 2020
Description: In recent years, emotion detection in text has become increasingly popular because of its many potential applications in a range of areas, such as marketing, political science, psychology, human-computer interaction, artificial intelligence. Acces...

Title: Detecting Discrete Emotions in Text Using Neural Networks
Author: Seyeditabari, Seyed Armin
Date Created: 2020
Subjects--Topical: Computer science, Artificial intelligence
Description: In recent years, emotion detection in text has become increasingly popular because of its many potential applications in a range of areas, such as marketing, political science, psychology, human-computer interaction, artificial intelligence. Acces...

Title: EXPERIMENTS IN TEXT SUMMARIZATION USING DEEP LEARNING
Author: Bulusu, Sai Amrit
Date Created: 2018
Description: Deep Learning has been the go-to tool for text summarization in the recent times.Traditional deep learning research focuses on performing abstractive text summarizationwithout considering the user’s interests to personalize the summaries.This prob...

Title: EXPERIMENTS IN TEXT SUMMARIZATION USING DEEP LEARNING
Author: Bulusu, Sai Amrit
Date Created: 2018
Subjects--Topical: Computer science, Artificial intelligence, Information science
Description: Deep Learning has been the go-to tool for text summarization in the recent times.Traditional deep learning research focuses on performing abstractive text summarizationwithout considering the user’s interests to personalize the summaries.This prob...

Title: Examining Untempered Social Media: Information Mutation on GAB.ai
Author: Muppalla, Sai Eshwar Prasad
Date Created: 2018
Description: Online social media often mirrors the social phenomenon of "Chinese Whispers" where information mutates during dissemination.Many a time, Twitter and Facebook in conjunction with smaller "fringe" communities like Gab.ai, often echo perspectives to...

Title: Examining Untempered Social Media: Information Mutation on GAB.ai
Author: Muppalla, Sai Eshwar Prasad
Date Created: 2018
Subjects--Topical: Computer science
Description: Online social media often mirrors the social phenomenon of "Chinese Whispers" where information mutates during dissemination.Many a time, Twitter and Facebook in conjunction with smaller "fringe" communities like Gab.ai, often echo perspectives to...

Title: Generative Machine Learning Models for Airflow Prediction of Architectural Spaces
Author: Claudio Rodriguez, Fernando
Date Created: 2021
Description: Computer Fluid Dynamics (CFD) airflow simulations are not used as often in architectural settings primarily due to time constraints. The proper use of CFD airflow simulations involves a complex setup and run-time process that requires a large amou...

Title: Generative Machine Learning Models for Airflow Prediction of Architectural Spaces
Author: Claudio Rodriguez, Fernando
Date Created: 2021
Subjects--Topical: Computer science, Information technology, Architecture
Description: Computer Fluid Dynamics (CFD) airflow simulations are not used as often in architectural settings primarily due to time constraints. The proper use of CFD airflow simulations involves a complex setup and run-time process that requires a large amou...

Title: Investigating the causal link between the stock market and Twitter sentiments using causality models and deep learning methods
Author: Seyeditabari, Narjessadat
Date Created: 2018
Description: An investment theory called the efficient market hypothesis (EMH) claims that it is impossible to outperform the market, and therefore, stocks always trade at a fair value. An important assumption of EMH is that all investors make decisions ration...

Title: Investigating the causal link between the stock market and Twitter sentiments using causality models and deep learning methods
Author: Seyeditabari, Narjessadat
Date Created: 2018
Description: An investment theory called the efficient market hypothesis (EMH) claims that it is impossible to outperform the market, and therefore, stocks always trade at a fair value. An important assumption of EMH is that all investors make decisions ration...

Title: Investigating the causal link between the stock market and Twitter sentiments using causality models and deep learning methods
Author: Seyeditabari, Narjessadat
Date Created: 2018
Subjects--Topical: Computer science, Artificial intelligence
Description: An investment theory called the efficient market hypothesis (EMH) claims that it is impossible to outperform the market, and therefore, stocks always trade at a fair value. An important assumption of EMH is that all investors make decisions ration...

Title: Sequence Prediction Applied to BIM Log Data, An Approach to Develop a Command Recommender System for BIM Software Application
Author: Radnia, Ashkan
Date Created: 2021
Description: Building Information Modeling has become an industry standard for designing, documenting, and collaborating within the architecture, engineering, and construction industry. Architects spend most of their time developing projects from the feasibili...

Title: Sequence Prediction Applied to BIM Log Data, An Approach to Develop a Command Recommender System for BIM Software Application
Author: Radnia, Ashkan
Date Created: 2021
Subjects--Topical: Computer science, Information technology, Architecture
Description: Building Information Modeling has become an industry standard for designing, documenting, and collaborating within the architecture, engineering, and construction industry. Architects spend most of their time developing projects from the feasibili...

Title: Spatially Explicit Hyperparameter Optimization for Neural Networks
Author: Zheng, Minrui
Date Created: 2020
Description: Neural networks as a commonly used machine learning algorithms, such as artificial neural networks (ANNs) and convolutional neural networks (CNNs), have been extensively used in GIScience domain to explore the nonlinear geographic phenomena. Howev...

Title: Spatially Explicit Hyperparameter Optimization for Neural Networks
Author: Zheng, Minrui
Date Created: 2020
Subjects--Topical: Geodesy
Description: Neural networks as a commonly used machine learning algorithms, such as artificial neural networks (ANNs) and convolutional neural networks (CNNs), have been extensively used in GIScience domain to explore the nonlinear geographic phenomena. Howev...

Title: TST-IOC: A Text Style Transfer-based Approach to Automatic Intervention of Online Offensive Content on Social Media to Improve Online Safety
Author: Liu, Zhihui
Date Created: 2023
Subjects--Topical: Computer science, Artificial intelligence
Description: Social media platforms such as Facebook, TikTok and Instagram have witnessed increasing use of offensive language by online users, which can be harmful to other users. Recently the continuance of the pandemic has propelled the propagation of offen...