2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

Technical Program

MLSP-47: Applications of Machine Learning

Session Type: Poster
Time: Friday, 11 June, 14:00 - 14:45
Location: Gather.Town
Session Chair: Rainer Martin, Ruhr-Universität Bochum
 
MLSP-47.1: INTEGRATED CLASSIFICATION AND LOCALIZATION OF TARGETS USING BAYESIAN FRAMEWORK IN AUTOMOTIVE RADARS
         Anand Dubey; Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
         Avik Santra; Infineon Technologies AG
         Jonas Fuchs; Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
         Maximilian Luebke; Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
         Robert Weigel; Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
         Fabian Lurz; Hamburg University of Technology
 
MLSP-47.2: A DNN AUTOENCODER FOR AUTOMOTIVE RADAR INTERFERENCE MITIGATION
         Shengyi Chen; Ruhr-Universität Bochum & HELLA GmbH & Co. KGaA
         Jalal Taghia; HELLA GmbH & Co. KGaA
         Tai Fei; HELLA GmbH & Co. KGaA
         Uwe Kühnau; HELLA GmbH & Co. KGaA
         Nils Pohl; Ruhr-Universität Bochum
         Rainer Martin; Ruhr-Universität Bochum
 
MLSP-47.3: DURAS: DEEP UNFOLDED RADAR SENSING USING DOPPLER FOCUSING
         Pranav Goyal; Indraprastha Institute of Information Technology Delhi
         Satish Mulleti; Weizmann Institute of Science
         Anubha Gupta; Indraprastha Institute of Information Technology Delhi
         Yonina C. Eldar; Weizmann Institute of Science
 
MLSP-47.4: NNAKF: A NEURAL NETWORK ADAPTED KALMAN FILTER FOR TARGET TRACKING
         Sami Jouaber; Mines ParisTech/Thales LAS
         Silvère Bonnabel; Mines ParisTech/UNC
         Santiago Velasco-Forero; Mines ParisTech
         Marion Pilté; Thales LAS
 
MLSP-47.5: MULTI-SAMPLE ONLINE LEARNING FOR SPIKING NEURAL NETWORKS BASED ON GENERALIZED EXPECTATION MAXIMIZATION
         Hyeryung Jang; Dongguk University
         Osvaldo Simeone; King's College London
 
MLSP-47.6: PROBABILISTIC GRAPH NEURAL NETWORKS FOR TRAFFIC SIGNAL CONTROL
         Ting Zhong; University of Electronic Science and Technology of China
         Zheyang Xu; University of Electronic Science and Technology of China
         Fan Zhou; University of Electronic Science and Technology of China