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Moving Learning Machine towards Fast Real-Time Applications: A High-Speed FPGA-Based Implementation of the OS-ELM Training Algorithm
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Online sequential condition prediction method of natural circulation systems based on EOS-ELM and phase space reconstruction
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Extreme learning machine: Theory and applications
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A study on effectiveness of extreme learning machine
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Ensemble of subset online sequential extreme learning machine for class imbalance and concept drift
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Kernel based online learning for imbalance multiclass classification
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Realtime training on mobile devices for face recognition applications
inferredcites →https://doi.org/10.1109/access.2017.2765626openalex-snapshot
Application of EOS-ELM With Binary Jaya-Based Feature Selection to Real-Time Transient Stability Assessment Using PMU Data
inferredcites →https://doi.org/10.1109/access.2018.2791579openalex-snapshot
Pedestrian Dead-Reckoning Indoor Localization Based on OS-ELM
inferredcites →https://doi.org/10.1109/ccdc.2011.5968244openalex-snapshot
The detection of solder joint defect and solar panel orientation based on ELM and robust least square fitting
inferredcites →https://doi.org/10.1109/icbbe.2011.5780179openalex-snapshot
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Constraint Online Sequential Extreme Learning Machine for lifelong indoor localization system
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A Sparse Coding Neural Network ASIC With On-Chip Learning for Feature Extraction and Encoding
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Extreme Learning Machines [Trends & Controversies]
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FPGA Implementation of the Multilayer Neural Network for the Speed Estimation of the Two-Mass Drive System
inferredcites →https://doi.org/10.1109/tii.2016.2554521openalex-snapshot
Support Tool for the Combined Software/Hardware Design of On-Chip ELM Training for SLFF Neural Networks
inferredcites →https://doi.org/10.1109/tnn.2006.880583openalex-snapshot
A Fast and Accurate Online Sequential Learning Algorithm for Feedforward Networks
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Attention-Mechanism-Containing Neural Networks for High-Resolution Remote Sensing Image Classification
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What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-031-50920-9_3openalex-snapshot
Hardware Implementation of MRO-ELM for Online Sequential Learning on FPGA
inferred← citeshttps://doi.org/10.1007/s00170-019-04142-xopenalex-snapshot
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Random-based networks with dropout for embedded systems
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A Design Strategy for the Efficient Implementation of Random Basis Neural Networks on Resource-Constrained Devices
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A Novel Systolic Parallel Hardware Architecture for the FPGA Acceleration of Feedforward Neural Networks
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An Overflow/Underflow-Free Fixed-Point Bit-Width Optimization Method for OS-ELM Digital Circuit
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SoC Design Based on a FPGA for a Configurable Neural Network Trained by Means of an EKF
inferred← citeshttps://doi.org/10.3390/electronics9010040openalex-snapshot
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Cholesky Factorization Based Online Sequential Extreme Learning Machines with Persistent Regularization and Forgetting Factor
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Online Learning Method for Drift and Imbalance Problem in Client Credit Assessment
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