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20232026
most citedElasticAI: Creating and Deploying Energy-Efficient Deep Learning Accelerator for Pervasive Computing

10 citations · 53 across the 17 of their papers we have counts for

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5 papers · 1 filter

cs.AR2026

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…

cs.AR2026★ 4 cited

Energy Efficient LSTM Accelerators for Embedded FPGAs through Parameterised Architecture Design

Chao Qian, Tianheng Ling, Gregor Schiele

Long Short-term Memory Networks (LSTMs) are a vital Deep Learning technique suitable for performing on-device time series analysis on local sensor data streams of embedded devices.…

cs.AR2024★ 10 cited

ElasticAI: Creating and Deploying Energy-Efficient Deep Learning Accelerator for Pervasive Computing

Chao Qian, Tianheng Ling, Gregor Schiele

Deploying Deep Learning (DL) on embedded end devices is a scorching trend in pervasive computing. Since most Microcontrollers on embedded devices have limited computing power, it i…

cs.AR2024★ 1 cited

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…

cs.AR2023★ 8 cited

Enhancing Energy-efficiency by Solving the Throughput Bottleneck of LSTM Cells for Embedded FPGAs

Chao Qian, Tianheng Ling, Gregor Schiele

To process sensor data in the Internet of Things(IoTs), embedded deep learning for 1-dimensional data is an important technique. In the past, CNNs were frequently used because they…