TH2.SC2.5
SINGLE GATE SPIKING RECURRENT NEURAL NETWORK FOR HISTOGRAM-LESS SINGLE-PHOTON DEPTH SENSING
Yijie Miao, Makoto Ikeda, The University of Tokyo, Japan
Session:
TH2.SC2: Applications of Machine Learning Lecture
Track:
SiG-DML - Signal and Data Analytics for Machine Learning
Location:
Saint Clair 2
Presentation Time:
Thu, 29 Aug, 15:20 - 15:40 France Time (UTC +1)
Session Co-Chairs:
Sundeep Prabhakar Chepuri, Indian Institute of Science and Pierre Borgnat, CNRS, ENS de Lyon
Presentation
Discussion
Resources
No resources available.
Session TH2.SC2
TH2.SC2.1: Deep Learning-Based ON/OFF Detection for Enhanced Energy Disaggregation
Nidhal BALTI, Baptiste VRIGNEAU, Pascal SCALART, Univ of Rennes, France
TH2.SC2.2: Generalized FDIA Detection in Power Dependent Electrified Transportation Systems
Shahriar Rahman Fahim, Rachad Atat, Cihat Kececi, Texas A&M University, United States; Abdulrahman Takiddin, Florida State University, United States; Muhammad Ismail, Tennessee Tech University, United States; Katherine R. Davis, Erchin Serpedin, Texas A&M University, United States
TH2.SC2.3: WAVEFIELD MAE: LEVERAGING LARGE VISION MODELS FOR ULTRASONIC WAVEFIELD PATTERN ANALYSIS
Jiaxing YE, Takumi Kobayashi, Nobuyuki Toyama, National Institute of Advanced Industrial Science and Technology, Japan, Japan
TH2.SC2.4: Generating synthetic data to train a deep unrolled network for Hyperspectral Unmixing
Rassim Hadjeres, Christophe Kervazo, Florence Tupin, Télécom Paris, France
TH2.SC2.5: SINGLE GATE SPIKING RECURRENT NEURAL NETWORK FOR HISTOGRAM-LESS SINGLE-PHOTON DEPTH SENSING
Yijie Miao, Makoto Ikeda, The University of Tokyo, Japan