activity
20182021
most citedA Countrywide Traffic Accident Dataset

55 citations · 89 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CR20211 cited

HASI: Hardware-Accelerated Stochastic Inference, A Defense Against Adversarial Machine Learning Attacks

Mohammad Hossein Samavatian, Saikat Majumdar, Kristin Barber +1

Deep Neural Networks (DNNs) are employed in an increasing number of applications, some of which are safety critical. Unfortunately, DNNs are known to be vulnerable to so-called adv…

cs.LG2019

Accident Risk Prediction based on Heterogeneous Sparse Data: New Dataset and Insights

Sobhan Moosavi, Mohammad Hossein Samavatian, Srinivasan Parthasarathy +2

Reducing traffic accidents is an important public safety challenge, therefore, accident analysis and prediction has been a topic of much research over the past few decades. Using s…

cs.DB201955 cited

A Countrywide Traffic Accident Dataset

Sobhan Moosavi, Mohammad Hossein Samavatian, Srinivasan Parthasarathy +1

Reducing traffic accidents is an important public safety challenge. However, the majority of studies on traffic accident analysis and prediction have used small-scale datasets with…

cs.DB201933 cited

Short and Long-term Pattern Discovery Over Large-Scale Geo-Spatiotemporal Data

Sobhan Moosavi, Mohammad Hossein Samavatian, Arnab Nandi +2

Pattern discovery in geo-spatiotemporal data (such as traffic and weather data) is about finding patterns of collocation, co-occurrence, cascading, or cause and effect between geos…

cs.NE2018

RNNFast: An Accelerator for Recurrent Neural Networks Using Domain Wall Memory

Mohammad Hossein Samavatian, Anys Bacha, Li Zhou +1

Recurrent Neural Networks (RNNs) are an important class of neural networks designed to retain and incorporate context into current decisions. RNNs are particularly well suited for…