361 citations
- Carnegie Mellon UniversityUS12 papers
- Stanford UniversityUS6 papers
- Google (United States)US5 papers
- University of WashingtonUS5 papers
- Amazon (United States)US4 papers
- Apple (Germany)DE4 papers
- Apple (Israel)IL4 papers
- Arizona State UniversityUS4 papers
- Centre National de la Recherche ScientifiqueFR4 papers
- Jet Propulsion LaboratoryUS4 papers
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- École Polytechnique Fédérale de LausanneCH3 papers
13 papers · 1 filter
Secure Ranging with IEEE 802.15.4z HRP UWB
Xiliang Luo, Cem Kalkanli, Hao Zhou +2
Secure ranging refers to the capability of upper-bounding the actual physical distance between two devices with reliability. This is essential in a variety of applications, includi…
MultiView Independent Component Analysis with Delays
Ambroise Heurtebise, Pierre Ablin, Alexandre Gramfort
Linear Independent Component Analysis (ICA) is a blind source separation technique that has been used in various domains to identify independent latent sources from observed signal…
Minireview on Disordered Optical Metasurfaces
P. Lalanne, A. Dmitriev, C. Rockstuhl +2
The use of coherent wave phenomena to enhance device performance is a cornerstone of modern optics. In juxtaposition to (locally) periodic metasurfaces, their disordered counterpar…
Model Compression in Practice: Lessons Learned from Practitioners Creating On-device Machine Learning Experiences
Fred Hohman, Mary Beth Kery, Donghao Ren +1
On-device machine learning (ML) promises to improve the privacy, responsiveness, and proliferation of new, intelligent user experiences by moving ML computation onto everyday perso…
AXNav: Replaying Accessibility Tests from Natural Language
Maryam Taeb, Amanda Swearngin, Eldon Schoop +3
Developers and quality assurance testers often rely on manual testing to test accessibility features throughout the product lifecycle. Unfortunately, manual testing can be tedious,…
SeMAnD: Self-Supervised Anomaly Detection in Multimodal Geospatial Datasets
Daria Reshetova, Swetava Ganguli, C. V. Krishnakumar Iyer +1
We propose a Self-supervised Anomaly Detection technique, called SeMAnD, to detect geometric anomalies in Multimodal geospatial datasets. Geospatial data comprises of acquired and…