Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Artificial neural networks for photonic applications—from algorithms to implementation: tutorial
This tutorial–review on applications of artificial neural networks in photonics targets a broad
audience, ranging from optical research and engineering communities to computer science …
audience, ranging from optical research and engineering communities to computer science …
Smart energy meters for smart grids, an internet of things perspective
Smart energy has evolved over the years to include multiple domains integrated across
multiple technology themes, such as electricity, smart grid, and logistics, linked through …
multiple technology themes, such as electricity, smart grid, and logistics, linked through …
A survey of neuromorphic computing and neural networks in hardware
CD Schuman, TE Potok, RM Patton, JD Birdwell… - ar** over dnn accelerators via reconfigurable interconnects
Deep neural networks (DNN) have demonstrated highly promising results across computer
vision and speech recognition, and are becoming foundational for ubiquitous AI. The …
vision and speech recognition, and are becoming foundational for ubiquitous AI. The …
Personalized long-and short-term preference learning for next POI recommendation
Next POI recommendation has been studied extensively in recent years. The goal is to
recommend next POI for users at specific time given users' historical check-in data …
recommend next POI for users at specific time given users' historical check-in data …
Deep neural network approximation for custom hardware: Where we've been, where we're going
Deep neural networks have proven to be particularly effective in visual and audio
recognition tasks. Existing models tend to be computationally expensive and memory …
recognition tasks. Existing models tend to be computationally expensive and memory …
C-LSTM: Enabling efficient LSTM using structured compression techniques on FPGAs
Recently, significant accuracy improvement has been achieved for acoustic recognition
systems by increasing the model size of Long Short-Term Memory (LSTM) networks …
systems by increasing the model size of Long Short-Term Memory (LSTM) networks …
Accelerating recurrent neural networks in analytics servers: Comparison of FPGA, CPU, GPU, and ASIC
Recurrent neural networks (RNNs) provide state-of-the-art accuracy for performing analytics
on datasets with sequence (eg, language model). This paper studied a state-of-the-art RNN …
on datasets with sequence (eg, language model). This paper studied a state-of-the-art RNN …
FPGA-based accelerator for long short-term memory recurrent neural networks
Long Short-Term Memory Recurrent neural networks (LSTM-RNNs) have been widely used
for speech recognition, machine translation, scene analysis, etc. Unfortunately, general …
for speech recognition, machine translation, scene analysis, etc. Unfortunately, general …
Hardware accelerators for recurrent neural networks on FPGA
Recurrent Neural Networks (RNNs) have the ability to retain memory and learn from data
sequences, which are fundamental for real-time applications. RNN computations offer …
sequences, which are fundamental for real-time applications. RNN computations offer …