Enabling Machine Learning on the Edge using SRAM Conserving Efficient Neural Networks Execution Approach

This publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) under Grant Number SFI/16/RC/3918 (Confirm) and also by a research grant from Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289 P2 (Insight), with both grants co-funded by the European Regional Development Fund.

[1]  John G. Breslin,et al.  Edge2Guard: Botnet Attacks Detecting Offline Models for Resource-Constrained IoT Devices , 2021, 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops).

[2]  Forrest N. Iandola,et al.  SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <1MB model size , 2016, ArXiv.

[3]  A. Robert Calderbank,et al.  DCFNet: Deep Neural Network with Decomposed Convolutional Filters , 2018, ICML.

[4]  Muhammad Intizar Ali,et al.  Adaptive Strategy to Improve the Quality of Communication for IoT Edge Devices , 2020, 2020 IEEE 6th World Forum on Internet of Things (WF-IoT).

[5]  Ran El-Yaniv,et al.  Binarized Neural Networks , 2016, ArXiv.

[6]  Bo Chen,et al.  MnasNet: Platform-Aware Neural Architecture Search for Mobile , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[7]  Peter Corcoran,et al.  Smart Speaker Design and Implementation with Biometric Authentication and Advanced Voice Interaction Capability , 2022, AICS.

[8]  Geoffrey E. Hinton,et al.  Distilling the Knowledge in a Neural Network , 2015, ArXiv.

[9]  Roberto Cipolla,et al.  PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[10]  John G. Breslin,et al.  SRAM optimized porting and execution of machine learning classifiers on MCU-based IoT devices: demo abstract , 2021, ICCPS.

[11]  John G. Breslin,et al.  TinyML Benchmark: Executing Fully Connected Neural Networks on Commodity Microcontrollers , 2021, 2021 IEEE 7th World Forum on Internet of Things (WF-IoT).

[12]  John G. Breslin,et al.  Ultra-fast Machine Learning Classifier Execution on IoT Devices without SRAM Consumption , 2021, 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops).

[13]  Muhammad Intizar Ali,et al.  RCE-NN: a five-stage pipeline to execute neural networks (CNNs) on resource-constrained IoT edge devices , 2020, IOT.

[14]  Muhammad Intizar Ali,et al.  Avoid Touching Your Face: A Hand-to-face 3D Motion Dataset (COVID-away) and Trained Models for Smartwatches , 2020, IOT Companion.

[15]  Dumitru Erhan,et al.  Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[16]  George Papandreou,et al.  Rethinking Atrous Convolution for Semantic Image Segmentation , 2017, ArXiv.

[17]  Quoc V. Le,et al.  EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks , 2019, ICML.

[18]  Vijay Vasudevan,et al.  Learning Transferable Architectures for Scalable Image Recognition , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[19]  Kilian Q. Weinberger,et al.  Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[20]  Bo Chen,et al.  Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[21]  Forrest N. Iandola,et al.  SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <1MB model size , 2016, ArXiv.

[22]  Song Han,et al.  MCUNet: Tiny Deep Learning on IoT Devices , 2020, NeurIPS.

[23]  Shuchang Zhou,et al.  EAST: An Efficient and Accurate Scene Text Detector , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[24]  Muhammad Intizar Ali,et al.  Edge2Train: a framework to train machine learning models (SVMs) on resource-constrained IoT edge devices , 2020, IOT.

[25]  John G. Breslin,et al.  OWSNet: Towards Real-time Offensive Words Spotting Network for Consumer IoT Devices , 2021, 2021 IEEE 7th World Forum on Internet of Things (WF-IoT).

[26]  J. Breslin,et al.  Demo Abstract: Porting and Execution of Anomalies Detection Models on Embedded Systems in IoT , 2021 .