S. Wang

Publications
Influence

VTR 7.0: Next Generation Architecture and CAD System for FPGAs

Jason Luu, Jeffrey B. Goeders, +11 authors Vaughn Betz
Computer Science
TRETS
1 June 2014

VTR can now generate a netlist of the final post-routed circuit which enables detailed simulation of a design for a variety of purposes. Expand

DeepVO: Towards end-to-end visual odometry with deep Recurrent Convolutional Neural Networks

S. Wang, Ronald Clark, Hongkai Wen, A. Trigoni
Computer Science
IEEE International Conference on Robotics and…
15 January 2017

This paper presents a novel end-to-end monocular VO algorithm based on Deep Learning based on deep Recurrent Convolutional Neural Networks. Expand

Safety Verification of Deep Neural Networks

X. Huang, M. Kwiatkowska, S. Wang, M. Wu
Computer Science, Mathematics
CAV
21 October 2016

We develop a novel automated verification framework for feed-forward multi-layer neural networks based on Satisfiability Modulo Theory (SMT). Expand

Optimal multipath congestion control and request forwarding in Information-Centric Networks

Giovanna Carofiglio, Massimo Gallo, L. Muscariello, M. Papalini, S. Wang
Computer Science
21st IEEE International Conference on Network…
1 October 2013

The evolution of the Internet into a distributed Information access system calls for a paradigm shift to enable an evolvable future network architecture. Expand

VidLoc: A Deep Spatio-Temporal Model for 6-DoF Video-Clip Relocalization

Ronald Clark, S. Wang, A. Markham, A. Trigoni, Hongkai Wen
Computer Science
IEEE Conference on Computer Vision and Pattern…
21 February 2017

We use temporal smoothness of image-sequences to improve the accuracy of 6-DoF camera re-localization. Expand

End-to-end, sequence-to-sequence probabilistic visual odometry through deep neural networks

S. Wang, Ronald Clark, Hongkai Wen, A. Trigoni
Computer Science
Int. J. Robotics Res.
1 April 2018

An end-to-end, sequence- to-sequence probabilistic visual odometry framework is proposed for the monocular VO based on deep recurrent convolutional neural networks. Expand

VINet: Visual-Inertial Odometry as a Sequence-to-Sequence Learning Problem

Ronald Clark, S. Wang, Hongkai Wen, A. Markham, A. Trigoni
Computer Science
AAAI
29 January 2017

In this paper we present an end-to-end trainable method for visual-inertial odometry which performs fusion of the data at an intermediate feature-representation level. Expand

Reinforced Self-Attention Network: a Hybrid of Hard and Soft Attention for Sequence Modeling

Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, S. Wang, C. Zhang
Computer Science
IJCAI
31 January 2018

In this paper, we integrate both soft and hard attention into one context fusion model, "reinforced self-attention (ReSA)", for the mutual benefit of each other. Expand

Multimodal sentiment analysis with word-level fusion and reinforcement learning

M. Chen, S. Wang, P. P. Liang, T. Baltrusaitis, Amir Zadeh, Louis-Philippe Morency
Computer Science, Mathematics
ICMI
3 November 2017

We propose the Gated Multimodal Embedding LSTM with Temporal Attention (GME-LSTM(A)) model that is composed of 2 modules. Expand

Fingerprint enhancement in the singular point area

S. Wang, Y. Wang
Computer Science
IEEE Signal Processing Letters
7 January 2004

We present a new method and design a new filter to enhance a fingerprint in the singular point area, and the time required for our algorithm is reduced. Expand

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