MP2a.1

Pixel-Based Similarities as an Alternative to Neural Data for Improving Convolutional Neural Network Adversarial Robustness

Elie Attias, Cengiz Pehlevan, Dina Obeid, Harvard University, United States
Session:
MP2a: Modeling and Signal Processing in Neuroscience Lecture
Track:
Biomedical Signal and Image Processing
Location:
Acacia
Presentation Time:
Mon, 27 Oct, 13:30 - 13:55 PT (UTC -8)
Session Chair:
Patrick Purdon, Stanford University
Presentation
Discussion
Resources
No resources available.
Session MP2a
MP2a.1: Pixel-Based Similarities as an Alternative to Neural Data for Improving Convolutional Neural Network Adversarial Robustness
Elie Attias, Cengiz Pehlevan, Dina Obeid, Harvard University, United States
MP2a.2: Enhanced Multi-Source Domain Adaptation for EEG Pattern Recognition via Source Selection and Distance Function Optimization
Koushik Roy, Qi Cheng, Md. Mahmudul Hasan, Oklahoma State University, United States
MP2a.3: EEG Artifact Removal Using Switching State Space Models
Tom Stone, Si Long Jenny Tou, Mingjian He, Stanford University, United States; Amanda Beck, Massachusetts Institute of Technology, United States; Patrick Purdon, Stanford University, United States
MP2a.4: Spiking Global Coherence Estimation
John Tauber, Emily Stephen, Boston University, United States
Contacts