Daniel E. Capecci
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View article: Investigating the Practicality of Existing Reinforcement Learning Algorithms: A Performance Comparison
Investigating the Practicality of Existing Reinforcement Learning Algorithms: A Performance Comparison Open
Abstract---Reinforcement learning (RL) has become more popular due to promising results in applications such as chat-bots, healthcare, and autonomous driving. However, one significant challenge in current RL research is the difficulty in u…
View article: Investigating the Practicality of Existing Reinforcement Learning Algorithms: A Performance Comparison
Investigating the Practicality of Existing Reinforcement Learning Algorithms: A Performance Comparison Open
Abstract---Reinforcement learning (RL) has become more popular due to promising results in applications such as chat-bots, healthcare, and autonomous driving. However, one significant challenge in current RL research is the difficulty in u…
View article: Framework for Automatic PCB Marking Detection and Recognition for Hardware Assurance
Framework for Automatic PCB Marking Detection and Recognition for Hardware Assurance Open
A Bill of Materials (BoM) is a list of all components on a printed circuit board (PCB). Since BoMs are useful for hardware assurance, automatic BoM extraction (AutoBoM) is of great interest to the government and electronics industry. To ac…
View article: Lumen: A machine learning framework to expose influence cues in texts
Lumen: A machine learning framework to expose influence cues in texts Open
Phishing and disinformation are popular social engineering attacks with attackers invariably applying influence cues in texts to make them more appealing to users. We introduce Lumen, a learning-based framework that exposes influence cues …
View article: A Survey and Perspective on Artificial Intelligence for Security-Aware Electronic Design Automation
A Survey and Perspective on Artificial Intelligence for Security-Aware Electronic Design Automation Open
Artificial intelligence (AI) and machine learning (ML) techniques have been increasingly used in several fields to improve performance and the level of automation. In recent years, this use has exponentially increased due to the advancemen…
View article: Semi-Supervised Semantic Annotator (S3A): Toward Efficient Semantic Labeling
Semi-Supervised Semantic Annotator (S3A): Toward Efficient Semantic Labeling Open
Most semantic image annotation platforms suffer severe bottlenecks when handling large images, complex regions of interest, or numerous distinct foreground regions in a single image. We have developed the Semi-Supervised Semantic Annotator…
View article: Lumen: A Machine Learning Framework to Expose Influence Cues in Text
Lumen: A Machine Learning Framework to Expose Influence Cues in Text Open
Phishing and disinformation are popular social engineering attacks with attackers invariably applying influence cues in texts to make them more appealing to users. We introduce Lumen, a learning-based framework that exposes influence cues …
View article: Susceptibility to Spear-Phishing Emails
Susceptibility to Spear-Phishing Emails Open
Phishing is fundamental to cyber attacks. This research determined the effect of Internet user age and email content such as weapons of influence (persuasive techniques that attackers can use to lure individuals to fall for an attack) and …