1 citations · 1 across the 3 of their papers we have counts for
8 papers
ViFi-Loc: Multi-modal Pedestrian Localization using GAN with Camera-Phone Correspondences
Hansi Liu, Kristin Dana, Marco Gruteser +1
In Smart City and Vehicle-to-Everything (V2X) systems, acquiring pedestrians' accurate locations is crucial to traffic safety. Current systems adopt cameras and wireless sensors to…
LaNet: Real-time Lane Identification by Learning Road SurfaceCharacteristics from Accelerometer Data
Madhumitha Harishankar, Jun Han, Sai Vineeth Kalluru Srinivas +7
The resolution of GPS measurements, especially in urban areas, is insufficient for identifying a vehicle's lane. In this work, we develop a deep LSTM neural network model LaNet tha…
Advances and Open Problems in Federated Learning
Peter Kairouz, H. Brendan McMahan, Brendan Avent +56
Federated learning (FL) is a machine learning setting where many clients (e.g. mobile devices or whole organizations) collaboratively train a model under the orchestration of a cen…
Federated Learning with Autotuned Communication-Efficient Secure Aggregation
Keith Bonawitz, Fariborz Salehi, Jakub Konečný +2
Federated Learning enables mobile devices to collaboratively learn a shared inference model while keeping all the training data on a user's device, decoupling the ability to do mac…
Sub-6GHz Assisted MAC for Millimeter Wave Vehicular Communications
Baldomero Coll-Perales, Javier Gozalvez, Marco Gruteser
Sub-6GHz vehicular communications (using DSRC, ITS-G5 or C-V2X) have been developed to support active safety applications. Future connected and automated driving applications can r…
Evaluation of IEEE 802.11ad for mmWave V2V Communications
Baldomero Coll-Perales, Marco Gruteser, Javier Gozalvez
Autonomous vehicles can construct a more accurate perception of their surrounding environment by exchanging rich sensor data with nearby vehicles. Such exchange can require larger…