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Exploring Transfer Learning Focused on Physiological Signals for Emotion Recognition
Recent work in the area of automatic emotion recognition has leveraged a large amount of publicly available data with transfer learning techniques to detect emotion on low-resource data. Previous work demonstrated that the ...
Don’t Lie To Me: Integrating Client-Side Web Scraping And Review Behavior Analysis To Detect Fake Reviews
User reviews are a widespread across the Internet as an indicator of the quality of a product. However, review systems can be vulnerable to attack. Malicious parties can manipulate the ratings of items by soliciting fake ...
Automated Cloud Removal on High-Altitude UAV Imagery Through Deep Learning on Synthetic Data
New theories and applications of deep learning have been discovered and implemented within the field of machine learning recently. The high degree of effectiveness of deep learning models span across many domains including ...
Reinforcement Learning For Collision Avoidance
(2015-09-23)
Autonomous travel poses challenges in machine learning navigation. Different approaches have been considered, such as reinforcement learning, dynamic programming methodologies, and other artificial intelligence assisted ...
Predicting Driver Distraction: An Analysis of Machine Learning Algorithms and Input Measures
(2018-04-26)
The research area on the detection and classification of distracted driving is growing in importance as in-vehicle information systems such as navigation and entertainment displays, which introduce sources of distraction ...
A Machine Learning Approach to Pitot Static Error Detection and Airspeed Prediction
(2016-08-17)
Aircraft guidance is dependent on various sensors which provide information on speed, altitude and location with respect to both the ground and the surrounding air. The pitot static system, global positioning system (GPS) ...
Price Discovery and Integration of the Peanut Markets in the United States
(2019-05-02)
Currently, the United States is a major supplier in the world peanut market. Using grower level monthly peanut price data from 1982-2018, this study estimates market integration and price discovery patterns among grower ...
RLDP: Reinforcement Learning Decision-Time Planner
Reinforcement learning (RL) is a state-of-the-art approach to solving sequential decision-making problems in stochastic environments. However, most model-free RL algorithms only produce one action at each timestep. That ...
Cyber-Physical Defense in Smart Distribution Networks
(2021-04-26)
The existing electric grid is transitioning to a smart grid with increased penetration of distributed energy resources (DERs), such as photovoltaic (PV) units, battery storage units, electric vehicles (EV), and EV chargers. ...
Machine Learning-Based Dynamic Voltage and Frequency Scaling Error Detection
Modern microprocessors are more and more optimized for speed and power efficiency. A system that regulates these parameters is Dynamic Voltage and Frequency Scaling (DVFS). Generally, all bugs or errors in a microarchitecture ...