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07/13/2023
A Case for Offloading Federated Learning Server on Smart NIC
Federated learning is a distributed machine learning approach where loca...
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06/30/2023
An Integrated FPGA Accelerator for Deep Learning-based 2D/3D Path Planning
Path planning is a crucial component for realizing the autonomy of mobil...
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12/19/2022
A Sequential Concept Drift Detection Method for On-Device Learning on Low-End Edge Devices
A practical issue of edge AI systems is that data distributions of train...
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08/19/2022
Communication Size Reduction of Federated Learning based on Neural ODE Model
Federated learning is a machine learning method in which data is not agg...
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03/11/2022
An Efficient Accelerator for Deep Learning-based Point Cloud Registration on FPGAs
Point cloud registration is the basis for many robotic applications such...
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03/02/2022
On-Device Learning: A Neural Network Based Field-Trainable Edge AI
In real-world edge AI applications, their accuracy is often affected by ...
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10/26/2021
A DPDK-Based Acceleration Method for Experience Sampling of Distributed Reinforcement Learning
A computing cluster that interconnects multiple compute nodes is used to...
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07/27/2021
A Low-Cost Neural ODE with Depthwise Separable Convolution for Edge Domain Adaptation on FPGAs
Although high-performance deep neural networks are in high demand in edg...
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03/17/2021
An Overflow/Underflow-Free Fixed-Point Bit-Width Optimization Method for OS-ELM Digital Circuit
Currently there has been increasing demand for real-time training on res...
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03/17/2021
Particle Filter-based vs. Graph-based: SLAM Acceleration on Low-end FPGAs
SLAM allows a robot to continuously perceive the surrounding environment...
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12/31/2020
Accelerating ODE-Based Neural Networks on Low-Cost FPGAs
ODENet is a deep neural network architecture in which a stacking structu...
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05/29/2020
An FPGA Acceleration and Optimization Techniques for 2D LiDAR SLAM Algorithm
An efficient hardware design of Simultaneous Localization and Mapping (S...
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05/10/2020
An FPGA-Based On-Device Reinforcement Learning Approach using Online Sequential Learning
DQN (Deep Q-Network) is a method to perform Q-learning for reinforcement...
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02/27/2020
An On-Device Federated Learning Approach for Cooperative Anomaly Detection
Most edge AI focuses on prediction tasks on resource-limited edge device...
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07/23/2019
A Neural Network Based On-device Learning Anomaly Detector for Edge Devices
Semi-supervised anomaly detection is referred as an approach to identify...
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05/29/2018
