Model compression and hardware acceleration for neural networks: A comprehensive survey
Domain-specific hardware is becoming a promising topic in the backdrop of improvement
slow down for general-purpose processors due to the foreseeable end of Moore's Law …
slow down for general-purpose processors due to the foreseeable end of Moore's Law …
A comprehensive survey on model compression and acceleration
T Choudhary, V Mishra, A Goswami… - Artificial Intelligence …, 2020 - Springer
In recent years, machine learning (ML) and deep learning (DL) have shown remarkable
improvement in computer vision, natural language processing, stock prediction, forecasting …
improvement in computer vision, natural language processing, stock prediction, forecasting …
Identification of fruit tree pests with deep learning on embedded drone to achieve accurate pesticide spraying
CJ Chen, YY Huang, YS Li, YC Chen, CY Chang… - IEEE …, 2021 - ieeexplore.ieee.org
Tessaratoma papillosa (Drury) first invaded Taiwan in 2009. Every year, T. papillosa causes
severe damage to the longan crops. Novel applications for edge intelligence are applied in …
severe damage to the longan crops. Novel applications for edge intelligence are applied in …
Recent advances in efficient computation of deep convolutional neural networks
Deep neural networks have evolved remarkably over the past few years and they are
currently the fundamental tools of many intelligent systems. At the same time, the …
currently the fundamental tools of many intelligent systems. At the same time, the …
Toward compact convnets via structure-sparsity regularized filter pruning
The success of convolutional neural networks (CNNs) in computer vision applications has
been accompanied by a significant increase of computation and memory costs, which …
been accompanied by a significant increase of computation and memory costs, which …
Hybrid precoding for multiuser millimeter wave massive MIMO systems: A deep learning approach
AM Elbir, AK Papazafeiropoulos - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
In multi-user millimeter wave (mmWave) multiple-input-multiple-output (MIMO) systems,
hybrid precoding is a crucial task to lower the complexity and cost while achieving a …
hybrid precoding is a crucial task to lower the complexity and cost while achieving a …
DeepMUSIC: Multiple signal classification via deep learning
AM Elbir - IEEE Sensors Letters, 2020 - ieeexplore.ieee.org
This letter introduces a deep learning (DL) framework for the classification of multiple signals
in direction finding (DF) scenario via sensor arrays. Previous works in DL context mostly …
in direction finding (DF) scenario via sensor arrays. Previous works in DL context mostly …
Delving deep into spatial pooling for squeeze-and-excitation networks
Abstract Squeeze-and-Excitation (SE) blocks have demonstrated significant accuracy gains
for state-of-the-art deep architectures by re-weighting channel-wise feature responses. The …
for state-of-the-art deep architectures by re-weighting channel-wise feature responses. The …
A tinyml platform for on-device continual learning with quantized latent replays
In the last few years, research and development on Deep Learning models & techniques for
ultra-low-power devices–in a word, TinyML–has mainly focused on a train-then-deploy …
ultra-low-power devices–in a word, TinyML–has mainly focused on a train-then-deploy …
Integration of accelerated deep neural network into power transformer differential protection
Differential protection scheme is the main protection scheme of power transformers, which
still holds the risk of sending false trips subject to inrush currents. This article aims to …
still holds the risk of sending false trips subject to inrush currents. This article aims to …