64 citations
- General Electric (United States)US2 papers
- Association for Computing MachineryUS1 paper
- Ben-Gurion University of the NegevIL1 paper
- Bielefeld UniversityDE1 paper
- California Southern UniversityUS1 paper
- Cardiff UniversityGB1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- General Motors (Poland)PL1 paper
- Google (United States)US1 paper
- Institut Jean Le Rond d'AlembertFR1 paper
- Jilin Medical UniversityCN1 paper
- Jilin UniversityCN1 paper
25 papers
BoostRad: Enhancing Object Detection by Boosting Radar Reflections
Yuval Haitman, Oded Bialer
Automotive radars have an important role in autonomous driving systems. The main challenge in automotive radar detection is the radar's wide point spread function (PSF) in the angu…
Influence of microstructure on mass loss caused by acoustic and hydrodynamic cavitation
Julien Hofmann, Charles Thiébaut, Michel Riondet +3
The proposed study investigates the damage mechanisms of martensitic stainless steel X3CrNiMo13-4 exposed to cavitation using two complementary experimental apparatus: ultrasonic h…
Adversarial Attacks with Time-Scale Representations
Alberto Santamaria-Pang, Jianwei Qiu, Aritra Chowdhury +4
We propose a novel framework for real-time black-box universal attacks which disrupts activations of early convolutional layers in deep learning models. Our hypothesis is that pert…
Parallel mesh reconstruction streams for pose estimation of interacting hands
Uri Wollner, Guy Ben-Yosef
We present a new multi-stream 3D mesh reconstruction network (MSMR-Net) for hand pose estimation from a single RGB image. Our model consists of an image encoder followed by a mesh-…
Learning How to Optimize Black-Box Functions With Extreme Limits on the Number of Function Evaluations
Carlos Ansotegui, Meinolf Sellmann, Tapan Shah +1
We consider black-box optimization in which only an extremely limited number of function evaluations, on the order of around 100, are affordable and the function evaluations must b…
Discovery of Physics and Characterization of Microstructure from Data with Bayesian Hidden Physics Models
Steven Atkinson, Yiming Zhang, Liping Wang
There has been a surge in the interest of using machine learning techniques to assist in the scientific process of formulating knowledge to explain observational data. We demonstra…