0% Complete
English
صفحه اصلی
/
سیزدهمین کنفرانس بین المللی فناوری اطلاعات و دانش
A Hybrid Method to Reduce the Voltage Consumption in the Spiking Neural Networks
نویسندگان :
Shaghayegh Mehdizadeh saraj
1
Seyyed Amir Asghari
2
Mohammadreza Binesh Marvasti
3
1- Kharazmi University
2- Kharazmi University
3- Kharazmi University
کلمات کلیدی :
Neuron threshold،Spiking Neural Networks،Time depend coding،Artifical intelligence
چکیده :
With artificial intelligence's tremendous progress in the past decades, the demand for applying artificial intelligence algorithms and architectures in cloud computing has increased. In this regard, the need for neuromorphic hardware that enables training and processing of data generated by edge devices has increased. Different algorithms have been presented in this direction, but they consume a lot of energy and space due to the large number of calculations. Therefore, researchers tried to minimize energy consumption while maintaining accuracy in deep spiking neural networks as the least consuming generation of neural networks. In order to achieve this goal and reduce the number of references to the required memory and space, they have provided various hardware and software methods. In this article, the best architecture is used by examining the amount of energy consumed and the accuracy of different methods of architecture. Also, a hybrid method is proposed to reduce energy consumption in spiking neural networks. The proposed hybrid architecture was implemented on the MNIST dataset, showing that the power consumption is reduced by almost 1% compared to the state-of-the-art architectures. The accuracy of the proposed hybrid algorithm is 95.3%, which is the highest when compared to the architectures using the time-based coding.
لیست مقالات
لیست مقالات بایگانی شده
Cryptanalysis of two password authenticated key exchange schemes
Mohammad Ali Poorafsahi - Hamid Mala
SPA Bot: Smart Price-Action Trading Bot for Cryptocurency Market
Dr Hamid Jazayeriy - Mohammad Daryani
Multi-Modal Longitudinal Tooth Labeling with Temporal Graph–Transformer Integration
Maral Mirza mohammadi - Mahdi Tarom
Targeted Vaccination for COVID-19 Using Mobile Communication Networks
Mohammadmohsen Jadidi - Pegah Moslemi - Saeed Jamshidiha - Iman Masroori - Abbas Mohammadi - Vahid Pourahmadi
Application of Artificial Intelligence and Remote Sensing for Oil Spill Detection
َAmir Reza Ziaee - Masomeh Azimzadeh - Parvin Ahmadi
An Improved Drone Detection Method Using Deep Learning for Augmentation Detection Speed
Mohammad Bahrami - Seyyed Amir Asghari - Mohammadreza Binesh Marvasti - Sajjad Ansaria
طراحی واسط کاربری مبتنی بر رفتار و احساسات کاربران در سیستم های هوشمند
فاطمه صبائی - دکتر احمد عبداله زاده بارفروش
کنترل کیفیت پیش_بینانه آمیزه_های لاستیکی مدلی یکپارچه بر اساس استاندارد پذیرش متغیرهای ANSI Z1.9 و پایش رئولوژیکی برخط
آکو یاری - فرهاد محمدزاده
ISAAF: بهبود چارچوب مجوز خودتطبیق SAAF با استفاده از پیادهسازی مبتنی بر عامل و مفهوم I-Shairing
الهام معین الدینی - دکتر منیره عبدوس - دکتر اسلام ناظمی
NFV-Based Distributed Service Function Chaining with Imperfect Information
Mahsa Alikhani - Marzieh Sheikhi - Dr Vesal Hakami
بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 42.5.2