5 citations · 5 across the 3 of their papers we have counts for
3 papers
Concept Drift Detection and Adaptive Retraining of Malware Classification Models
Christofer Washington Berruz Chungata, Martin Jurecek, Katerina Potika +2
Concept drift refers to changes over time in the statistical properties of data, as compared to the data that was used to train a learning model. Machine learning models for malwar…
AGRO: An Autonomous AI Rover for Precision Agriculture
Simar Ghumman, Fabio Di Troia, William Andreopoulos +2
Unmanned Ground Vehicles (UGVs) are emerging as a crucial tool in the world of precision agriculture. The combination of UGVs with machine learning allows us to find solutions for…
CNN vs ELM for Image-Based Malware Classification
Mugdha Jain, William Andreopoulos, Mark Stamp
Research in the field of malware classification often relies on machine learning models that are trained on high-level features, such as opcodes, function calls, and control flow g…