7 citations · 21 across the 12 of their papers we have counts for
12 papers
KANLib -- A Modular, Extensible and Fast Kolmogorov-Arnold Network Implementation
Julian Hoever, Gregor Schiele
Kolmogorov-Arnold Networks (KANs) have recently emerged as a promising alternative to traditional multilayer perceptrons by replacing linear weights with learnable univariate funct…
A Resilient Solution for Sewer Overflow Monitoring across Cloud and Edge
Vipin Singh, Tianheng Ling, Peter Ghaly +3
Aging combined sewer systems in many historical cities are increasingly stressed by extreme rainfall events, which can trigger combined sewer overflows (CSO) with significant envir…
Towards an End-To-End System for Real-Time Gesture Recognition from Surface Vibrations
Florian Hettstedt, Cedric Giese, Tianheng Ling +3
Sensing surface vibrations promise unobtrusive interaction for smart home systems by enabling gesture recognition on existing everyday surfaces without disturbing living-space desi…
StrikeWatch: Wrist-worn Gait Recognition with Compact Time-series Models on Low-power FPGAs
Tianheng Ling, Chao Qian, Peter Zdankin +2
Running offers substantial health benefits, but improper gait patterns can lead to injuries, particularly without expert feedback. While prior gait analysis systems based on camera…
Enabling Vibration-Based Gesture Recognition on Everyday Furniture via Energy-Efficient FPGA Implementation of 1D Convolutional Networks
Koki Shibata, Tianheng Ling, Chao Qian +4
The growing demand for smart home interfaces has increased interest in non-intrusive sensing methods like vibration-based gesture recognition. While prior studies demonstrated feas…
Automated Energy-Aware Time-Series Model Deployment on Embedded FPGAs for Resilient Combined Sewer Overflow Management
Tianheng Ling, Vipin Singh, Chao Qian +2
Extreme weather events, intensified by climate change, increasingly challenge aging combined sewer systems, raising the risk of untreated wastewater overflow. Accurate forecasting…
Automating Versatile Time-Series Analysis with Tiny Transformers on Embedded FPGAs
Tianheng Ling, Chao Qian, Lukas Johannes Haßler +1
Transformer-based models have shown strong performance across diverse time-series tasks, but their deployment on resource-constrained devices remains challenging due to high memory…
Resource-aware Mixed-precision Quantization for Enhancing Deployability of Transformers for Time-series Forecasting on Embedded FPGAs
Tianheng Ling, Chao Qian, Gregor Schiele
This study addresses the deployment challenges of integer-only quantized Transformers on resource-constrained embedded FPGAs (Xilinx Spartan-7 XC7S15). We enhanced the flexibility…
An Automated Approach to Collecting and Labeling Time Series Data for Event Detection Using Elastic Node Hardware
Tianheng Ling, Islam Mansour, Chao Qian +1
Recent advancements in IoT technologies have underscored the importance of using sensor data to understand environmental contexts effectively. This paper introduces a novel embedde…
Idle is the New Sleep: Configuration-Aware Alternative to Powering Off FPGA-Based DL Accelerators During Inactivity
Chao Qian, Christopher Cichiwskyj, Tianheng Ling +1
In the rapidly evolving Internet of Things (IoT) domain, we concentrate on enhancing energy efficiency in Deep Learning accelerators on FPGA-based heterogeneous platforms, aligning…
Integer-only Quantized Transformers for Embedded FPGA-based Time-series Forecasting in AIoT
Tianheng Ling, Chao Qian, Gregor Schiele
This paper presents the design of a hardware accelerator for Transformers, optimized for on-device time-series forecasting in AIoT systems. It integrates integer-only quantization…
Towards Auto-Building of Embedded FPGA-based Soft Sensors for Wastewater Flow Estimation
Tianheng Ling, Chao Qian, Gregor Schiele
Executing flow estimation using Deep Learning (DL)-based soft sensors on resource-limited IoT devices has demonstrated promise in terms of reliability and energy efficiency. Howeve…