178 citations · 347 across the 23 of their papers we have counts for
4 papers · 1 filter
Positional Embedding-Aware Activations
Kathan Shah, Chawin Sitawarin
We present a neural network architecture designed to naturally learn a positional embedding and overcome the spectral bias towards lower frequencies faced by conventional activatio…
REAP: A Large-Scale Realistic Adversarial Patch Benchmark
Nabeel Hingun, Chawin Sitawarin, Jerry Li +1
Machine learning models are known to be susceptible to adversarial perturbation. One famous attack is the adversarial patch, a sticker with a particularly crafted pattern that make…
Part-Based Models Improve Adversarial Robustness
Chawin Sitawarin, Kornrapat Pongmala, Yizheng Chen +2
We show that combining human prior knowledge with end-to-end learning can improve the robustness of deep neural networks by introducing a part-based model for object classification…
Beyond Grand Theft Auto V for Training, Testing and Enhancing Deep Learning in Self Driving Cars
Mark Martinez, Chawin Sitawarin, Kevin Finch +3
As an initial assessment, over 480,000 labeled virtual images of normal highway driving were readily generated in Grand Theft Auto V's virtual environment. Using these images, a CN…