235 citations · 531 across the 38 of their papers we have counts for
9 papers · 1 filter
A Customizable Dynamic Scenario Modeling and Data Generation Platform for Autonomous Driving
Jay Shenoy, Edward Kim, Xiangyu Yue +4
Safely interacting with humans is a significant challenge for autonomous driving. The performance of this interaction depends on machine learning-based modules of an autopilot, suc…
Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation
Sicheng Zhao, Xuanbai Chen, Xiangyu Yue +7
Thanks to large-scale labeled training data, deep neural networks (DNNs) have obtained remarkable success in many vision and multimedia tasks. However, because of the presence of d…
Scenic: A Language for Scenario Specification and Data Generation
Daniel J. Fremont, Edward Kim, Tommaso Dreossi +4
We propose a new probabilistic programming language for the design and analysis of cyber-physical systems, especially those based on machine learning. Specifically, we consider the…
The Quotient in Preorder Theories
Íñigo X. Íncer Romeo, Leonardo Mangeruca, Tiziano Villa +1
Seeking the largest solution to an expression of the form A x <= B is a common task in several domains of engineering and computer science. This largest solution is commonly called…
A Review of Single-Source Deep Unsupervised Visual Domain Adaptation
Sicheng Zhao, Xiangyu Yue, Shanghang Zhang +8
Large-scale labeled training datasets have enabled deep neural networks to excel across a wide range of benchmark vision tasks. However, in many applications, it is prohibitively e…
Generalizing Fault Detection Against Domain Shifts Using Stratification-Aware Cross-Validation
Yingshui Tan, Baihong Jin, Qiushi Cui +2
Incipient anomalies present milder symptoms compared to severe ones, and are more difficult to detect and diagnose due to their close resemblance to normal operating conditions. Th…
Using Ensemble Classifiers to Detect Incipient Anomalies
Baihong Jin, Yingshui Tan, Albert Liu +3
Incipient anomalies present milder symptoms compared to severe ones, and are more difficult to detect and diagnose due to their close resemblance to normal operating conditions. Th…
Are Ensemble Classifiers Powerful Enough for the Detection and Diagnosis of Intermediate-Severity Faults?
Baihong Jin, Yingshui Tan, Yuxin Chen +2
Intermediate-Severity (IS) faults present milder symptoms compared to severe faults, and are more difficult to detect and diagnose due to their close resemblance to normal operatin…
Industrial Control via Application Containers:Maintaining determinism in IAAS
Florian Hofer, Martin Sehr, Alberto Sangiovanni-Vincentelli +1
Industry 4.0 is changing fundamentally data collection, its storage and analysis in industrial processes, enabling novel application such as flexible manufacturing of highly custom…