113 citations · 387 across the 19 of their papers we have counts for
19 papers
Real-Time Wearable Gait Phase Segmentation For Running And Walking
Jien-De Sui, Wei-Han Chen, Tzyy-Yuang Shiang +1
Previous gait phase detection as convolutional neural network (CNN) based classification task requires cumbersome manual setting of time delay or heavy overlapped sliding windows t…
Deep Gait Tracking With Inertial Measurement Unit
Jien De Sui, Tian Sheuan Chang
This paper presents a convolutional neural network based foot motion tracking with only six-axis Inertial-Measurement-Unit (IMU) sensor data. The presented approach can adapt to va…
Row-wise Accelerator for Vision Transformer
Hong-Yi Wang, Tian-Sheuan Chang
Following the success of the natural language processing, the transformer for vision applications has attracted significant attention in recent years due to its excellent performan…
A Real Time Super Resolution Accelerator with Tilted Layer Fusion
An-Jung Huang, Kai-Chieh Hsu, Tian-Sheuan Chang
Deep learning based superresolution achieves high-quality results, but its heavy computational workload, large buffer, and high external memory bandwidth inhibit its usage in mobil…
Hardware-Robust In-RRAM-Computing for Object Detection
Yu-Hsiang Chiang, Cheng En Ni, Yun Sung +3
In-memory computing is becoming a popular architecture for deep-learning hardware accelerators recently due to its highly parallel computing, low power, and low area cost. However,…
IMU Based Deep Stride Length Estimation With Self-Supervised Learning
Jien-De Sui, Tian-Sheuan Chang
Stride length estimation using inertial measurement unit (IMU) sensors is getting popular recently as one representative gait parameter for health care and sports training. The tra…