Mary L. Comer
Computer Science · Purdue University West Lafayette
Publications
106
Citations
1,222
Est. group size
~5
Recurring co-author estimate
Active years
34
Publishing since 1992
Mary L. Comer works on signal processing and machine learning methods applied to problems such as anomaly detection in spacecraft telemetry, hypersonic vehicle trajectory prediction, remote sensing image analysis, and object localization in noisy imagery. Much of the work involves developing statistical models (such as Markov random fields and stochastic grammars) and machine learning approaches (including neural networks and transfer learning) for detecting unusual patterns or classifying behavior in time-series and image data. The research has practical applications in aerospace monitoring, satellite imagery analysis, and defense-related trajectory prediction.
Publication output rose from a low level in 2017 to a peak in 2021, then has fluctuated at a somewhat lower and more variable pace through 2025.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Spacecraft Multivariate Time Series Anomaly Detection in the Presence of Non-Anomalous Spikes
2025
- Asymptotically Efficient Simulation and Modeling of Rare Binary Images
Electronic Imaging · 2025
- A Graph Neural Network for Anomaly Detection in Multi-Channel Time Series Data
2025
- Multichannel Anomaly Detection for Spacecraft Time Series Using MAP Estimation
IEEE Transactions on Aerospace and Electronic Systems · 2024
- Predicting Hypersonic Glide Vehicle Behavior With Stochastic Grammars
IEEE Transactions on Aerospace and Electronic Systems · 2023
- Spacecraft Time-Series Online Anomaly Detection Using Deep Learning
2023
- A Two-Stage Road Segmentation Approach for Remote Sensing Images
Lecture notes in computer science · 2023
- Transfer Learning for Hypersonic Vehicle Trajectory Prediction
2023
- Object Localization in the Presence of Noise
2023
- A Machine Learning Method for Object Localization
2023
- Infrared Small Target Detection Enhancement Using a Lightweight Convolutional Neural Network
IEEE Geoscience and Remote Sensing Letters · 2022
- Spacecraft Time-Series Online Anomaly Detection Using Extreme Learning Machines
2022 IEEE Aerospace Conference (AERO) · 2022
- A Matching-Based Method for Anomaly Verification in Spacecraft Telemetry
2022 IEEE Aerospace Conference (AERO) · 2022
- A Stochastic Grammar Approach to Predict Flight Phases of a Hypersonic Glide Vehicle
2022 IEEE Aerospace Conference (AERO) · 2022
- Sub-Pixel Localization of Objects Using Multiple Spectral Bands
2022 IEEE Aerospace Conference (AERO) · 2022
- Electronic Imaging×6
- 2022 IEEE Aerospace Conference (AERO)×4
- IEEE Transactions on Aerospace and Electronic Systems×2
- IEEE Transactions on Computational Imaging×2
- IEEE Signal Processing Magazine×2
- Md Adnan Faisal Hossain
Computer Science · Purdue University West Lafayette
- Michael Gallant
Computer Science · Indiana University
- Zhihao Duan
Computer Science · Purdue University West Lafayette
- Yuning Huang
Computer Science · Purdue University West Lafayette
- Amy R. Reibman
Computer Science · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
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