4 citations · 6 across the 6 of their papers we have counts for
6 papers
AERO: Adaptive and Efficient Runtime-Aware OTA Updates for Energy-Harvesting IoT
Wei Wei, Jingye Xu, Sahidul Islam +3
Energy-harvesting (EH) Internet of Things (IoT) devices operate under intermittent energy availability, which disrupts task execution and makes energy-intensive over-the-air (OTA)…
Energy-Adaptive Checkpoint-Free Intermittent Inference for Low Power Energy Harvesting Systems
Sahidul Islam, Wei Wei, Jishnu Banarjee +1
Deep neural network (DNN) inference in energy harvesting (EH) devices poses significant challenges due to resource constraints and frequent power interruptions. These power losses…
Energy-aware Incremental OTA Update for Flash-based Batteryless IoT Devices
Wei Wei, Jishnu Banerjee, Sahidul Islam +2
Over-the-air (OTA) firmware updates are essential for updating and maintaining IoT devices, especially those batteryless devices reliant on energy harvesting power sources. Flash m…
EVE: Environmental Adaptive Neural Network Models for Low-power Energy Harvesting System
Sahidul Islam, Shanglin Zhou, Ran Ran +4
IoT devices are increasingly being implemented with neural network models to enable smart applications. Energy harvesting (EH) technology that harvests energy from ambient environm…
Enabling Fast Deep Learning on Tiny Energy-Harvesting IoT Devices
Sahidul Islam, Jieren Deng, Shanglin Zhou +3
Energy harvesting (EH) IoT devices that operate intermittently without batteries, coupled with advances in deep neural networks (DNNs), have opened up new opportunities for enablin…
Binary Complex Neural Network Acceleration on FPGA
Hongwu Peng, Shanglin Zhou, Scott Weitze +9
Being able to learn from complex data with phase information is imperative for many signal processing applications. Today' s real-valued deep neural networks (DNNs) have shown effi…