CNN

The goal of this project is to create a scalable and robust cyber-physical system (CPS) framework for the observation and control of the functional interdependencies between bridge structures (stationary physical systems) and trucks (mobile physical agents). A CPS framework (Figure 1) is being developed to monitor and control trucks within a single highway corridor to manage the imposed loads and the consumption of structural life by trucks on highway infrastructure including bridges.

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Object-Specific Style Transfer Based on Feature Map Selection Using CNNs

Submitted by grigby1 on Mon, 11/19/2018 - 12:29pm

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Deep Semantic Hashing with Generative Adversarial Networks

Submitted by grigby1 on Mon, 11/19/2018 - 12:23pm

Cyber-Physical Systems Virtual Organization

Fostering collaboration among CPS professionals in academia, government, and industry

Classifying Malware Using Convolutional Gated Neural Network

Malware Classification with Deep Convolutional Neural Networks

Low-Cost Breaking of a Unique Chinese Language CAPTCHA Using Curriculum Learning and Clustering

A Text-Based CAPTCHA Cracking System with Generative Adversarial Networks

Convolutional Neural Network Based SMS Spam Detection

CNN-Based Steganalysis of MP3 Steganography in the Entropy Code Domain

Android Malware Detection Using Convolutional Neural Networks and Data Section Images

Corridor-based Monitoring of Highway Bridge Health Condition and Truck Loads using a Cyber-Physical System Framework

Object-Specific Style Transfer Based on Feature Map Selection Using CNNs

Deep Semantic Hashing with Generative Adversarial Networks