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1. PolliSense: A Vision-Based Ecological Feature Extraction and Preference Learning for Pollinator Habitat Assessment

restricted_to_institution
Restricted (Penn State Only)
Author:
Adler, Sabrina
Title:
PolliSense: A Vision-Based Ecological Feature Extraction and Preference Learning for Pollinator Habitat Assessment
Area of Honors:
Computer Science
Keywords:
Computer vision
Machine learning
Pollinator habitat quality
Ecological feature extraction
Pairwise ranking
Preference learning
Habitat classification
Self-supervised learning
Thesis Supervisors:
Mehrdad Mahdavi, Thesis Supervisor
Martin Fürer, Thesis Honors Advisor

2. Quality Management for A&R: Designing, Controlling, and Improving the Music Hit-Vetting Process with Machine Learning

open_access
Open Access
Author:
Badamo, Hunter
Title:
Quality Management for A&R: Designing, Controlling, and Improving the Music Hit-Vetting Process with Machine Learning
Area of Honors:
Business Analytics & Information Systems
Keywords:
Machine learning
music industry
A&R
Hit prediction
Audio similarity
Music information retrieval
MIR
Music metadata
Quality management
Quality Function Deployment
House of Quality
QM
QFD
PANNs
Embedding models
Music analytics
Spotify
Spotify data
Predictive analytics
FAISS
Decision support systems
Business analytics
Thesis Supervisors:
Ferdi Eruysal, Thesis Supervisor
Suresh Muthulingam, Thesis Honors Advisor
Kevin Linderman, Faculty Reader