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
Ferroelectric-based synapses and neurons for neuromorphic computing
The shift towards a distributed computing paradigm, where multiple systems acquire and
elaborate data in real-time, leads to challenges that must be met. In particular, it is becoming …
elaborate data in real-time, leads to challenges that must be met. In particular, it is becoming …
A systematic literature review on binary neural networks
This paper presents an extensive literature review on Binary Neural Network (BNN). BNN
utilizes binary weights and activation function parameters to substitute the full-precision …
utilizes binary weights and activation function parameters to substitute the full-precision …
Bayesian multi-objective hyperparameter optimization for accurate, fast, and efficient neural network accelerator design
In resource-constrained environments, such as low-power edge devices and smart sensors,
deploying a fast, compact, and accurate intelligent system with minimum energy is …
deploying a fast, compact, and accurate intelligent system with minimum energy is …
A 55nm, 0.4 V 5526-TOPS/W compute-in-memory binarized CNN accelerator for AIoT applications
Binarized convolutional neural network (BCNN) is a promising and efficient technique
toward the landscape of Artificial Intelligence of Things (AIoT) applications. In-Memory …
toward the landscape of Artificial Intelligence of Things (AIoT) applications. In-Memory …
Exploring liquid neural networks on loihi-2
This study investigates the realm of liquid neural networks (LNNs) and their deployment on
neuromorphic hardware platforms. It provides an in-depth analysis of Liquid State Machines …
neuromorphic hardware platforms. It provides an in-depth analysis of Liquid State Machines …
Tactile surface roughness categorization with multineuron spike train distance
Tactile sensing with spiking neural networks (SNNs) has attracted increasing attention in the
past decades. In this article, a novel SNN framework is proposed for the tactile surface …
past decades. In this article, a novel SNN framework is proposed for the tactile surface …
Challenges and perspectives for energy-efficient brain-inspired edge computing applications
In recent years, Artificial Intelligence has shifted towards edge computing paradigm, where
systems compute data in real-time on the edge of the network, close to the sensor that …
systems compute data in real-time on the edge of the network, close to the sensor that …
[HTML][HTML] Hybrid stochastic synapses enabled by scaled ferroelectric field-effect transistors
Achieving brain-like density and performance in neuromorphic computers necessitates
scaling down the size of nanodevices emulating neuro-synaptic functionalities. However …
scaling down the size of nanodevices emulating neuro-synaptic functionalities. However …
Machine learning using magnetic stochastic synapses
The impressive performance of artificial neural networks has come at the cost of high energy
usage and CO 2 emissions. Unconventional computing architectures, with magnetic systems …
usage and CO 2 emissions. Unconventional computing architectures, with magnetic systems …
Efficient neuromorphic hardware through spiking temporal online local learning
Local learning schemes have shown promising performance in spiking neural networks
(SNNs) training and are considered a step toward more biologically plausible learning …
(SNNs) training and are considered a step toward more biologically plausible learning …