11 citations · 24 across the 41 of their papers we have counts for
13 papers · 1 filter
FOLIO: Focused Semantic Memory for Streaming Video Understanding
Haoyang Fan, Dhruv Parikh, Anvitha Ramachandran +4
In online streaming video understanding, a video stream continues to arrive and queries may be issued at any time. Because streaming frames grow without bound, the system must cont…
Vision Non-Causal Trapezoidal Mamba: Eliminating Directional Scanning in Vision SSMs with Second-Order Dynamics
Anvitha Ramachandran, Dhruv Parikh, Haoyang Fan +2
State Space Models (SSMs) have emerged as an alternative to Vision Transformers, yet most vision SSMs inherit directional token scanning from causal sequence modeling. While effect…
Can Graphs Help Vision SSMs See Better?
Dhruv Parikh, Anvitha Ramachandran, Haoyang Fan +3
Vision state space models inherit the efficiency and long-range modeling ability of Mamba-style selective scans. However, their performance depends critically on the representation…
Latent Denoising Improves Visual Alignment in Large Multimodal Models
Dhruv Parikh, Jacob Fein-Ashley, Rajgopal Kannan +1
Large Multimodal Models (LMMs) such as LLaVA are typically trained with an autoregressive language modeling objective, providing only indirect supervision to visual tokens. This of…
ConsensusDrop: Fusing Visual and Cross-Modal Saliency for Efficient Vision Language Models
Dhruv Parikh, Haoyang Fan, Rajgopal Kannan +1
Vision-Language Models (VLMs) are expensive because the LLM processes hundreds of largely redundant visual tokens. Existing token reduction methods typically exploit \textit{either…
ClusterViG: Efficient Globally Aware Vision GNNs via Image Partitioning
Dhruv Parikh, Jacob Fein-Ashley, Tian Ye +2
Convolutional Neural Networks (CNN) and Vision Transformers (ViT) have dominated the field of Computer Vision (CV). Graph Neural Networks (GNN) have performed remarkably well acros…
Studying the Effects of Self-Attention on SAR Automatic Target Recognition
Jacob Fein-Ashley, Rajgopal Kannan, Viktor Prasanna
Attention mechanisms are critically important in the advancement of synthetic aperture radar (SAR) automatic target recognition (ATR) systems. Traditional SAR ATR models often stru…
VTR: An Optimized Vision Transformer for SAR ATR Acceleration on FPGA
Sachini Wickramasinghe, Dhruv Parikh, Bingyi Zhang +3
Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) is a key technique used in military applications like remote-sensing image recognition. Vision Transformers (ViTs)…
FACTUAL: A Novel Framework for Contrastive Learning Based Robust SAR Image Classification
Xu Wang, Tian Ye, Rajgopal Kannan +1
Deep Learning (DL) Models for Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR), while delivering improved performance, have been shown to be quite vulnerable to ad…
Uncertainty-Aware SAR ATR: Defending Against Adversarial Attacks via Bayesian Neural Networks
Tian Ye, Rajgopal Kannan, Viktor Prasanna +1
Adversarial attacks have demonstrated the vulnerability of Machine Learning (ML) image classifiers in Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) systems. An…
A Single Graph Convolution Is All You Need: Efficient Grayscale Image Classification
Jacob Fein-Ashley, Sachini Wickramasinghe, Bingyi Zhang +2
Image classifiers for domain-specific tasks like Synthetic Aperture Radar Automatic Target Recognition (SAR ATR) and chest X-ray classification often rely on convolutional neural n…
Benchmarking Deep Learning Classifiers for SAR Automatic Target Recognition
Jacob Fein-Ashley, Tian Ye, Rajgopal Kannan +2
Synthetic Aperture Radar SAR Automatic Target Recognition ATR is a key technique of remote-sensing image recognition which can be supported by deep neural networks The existing wor…
Realistic Scatterer Based Adversarial Attacks on SAR Image Classifiers
Tian Ye, Rajgopal Kannan, Viktor Prasanna +2
Adversarial attacks have highlighted the vulnerability of classifiers based on machine learning for Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) tasks. An adve…