0% Complete
صفحه اصلی
/
سی و سومین کنفرانس بین المللی مهندسی برق
Classifier Fusion Based on Extracted Features Using a Spiking Neural Network from Handwritten Digits
نویسندگان :
Ali Gholamzade Fard Kazzazi
1
Malihe Nazari
2
Fariba Bahrami
3
1- دانشگاه صنعتی امیرکبیر
2- دانشگاه تهران
3- دانشگاه تهران
کلمات کلیدی :
spiking neural network،spike timing dependent plasticity،unsupervised learning،feature extraction،classification،classical classifiers،classifier fusion
چکیده :
The third generation of neural networks, known as spiking neural networks (SNNs), are capable of solving all problems that traditional networks can solve, and computationally, they can perform even more powerfully. Spiking neurons are closer to biological reality. For these reasons, these networks have gained significant attention in recent years. When using these networks for tasks such as pattern recognition or classification, there is no precise method for data classification. In previous works that employed spiking neural networks for classification, each approach generally utilized the unsupervised learning mechanisms that existed in these networks to classify the data through different techniques. Due to the weaknesses in the classification layer of spiking neural networks, we turned to the use of the firing rates of spiking neurons to extract features, which were then passed to classical classifiers. When we used spiking neurons for classification, we achieved an accuracy of 80.17%, and when we added a classical classifier in the third layer of the network, the accuracy increased to 84.48%. Based on the results obtained, the use of a classical classifier layer improved the network's accuracy. Additionally, it increased the execution speed compared to the case where a spiking neuron layer was used in the classification layer, and it reduced the need for extensive hyperparameter tuning of the SNN. Finally, we applied the Decision Template method for classifier fusion, which led to an accuracy of 84.87%. The results show that using classifier fusion methods improves the performance of the network.
لیست مقالات
لیست مقالات بایگانی شده
تشخیص انتها به انتها حملات جعل بازپخش صدا به کمک شبکه CNN-ViT جهت بهبود تعمیم پذیری
حسین حجازی - محمد عسگری
Design of a High-Efficiency RF Energy Harvesting System
Saeed Abbasi FallahPour - Shokrollah Karimian - ٍEsfandiar Mehrshahi
Automotive radar target classification using micro-Doppler features
Amin Aghatabarroodbary - Mohammad Hassan Bastani - Fereidoon Behnia
40Hz Auditory Entrainment Promotes Synchronization Between Frontal and Parietal Regions of the Brain
Mojtaba Lahijanian - Hamid Aghajan
Compare of Machine Learning and Deep Learning Approaches for Human Activity Recognition
Babak Moradi - Mohammad Aghapour - Afshin Shirbandi
Effect of the Number of Quantum-Dot Layers on the Performance of the 1.3 µm InAs/GaAs VCSELs
Sara Alaei - Mahmood Seifouri - Saeed Olyaee - Gholamreza Babaabbasi
Modeling of dielectrophoretic single-stage continuous separation of Escherichia coli K38 in a microfluidic channel
Saeed Saedy - Navid Alaei Sheini - Shahrzad Ajabi
Adaptive Control of Switched Nonlinear Systems with Unknown Control Directions
ٍElham Ovaysi - Marzieh Kamali
Experimental Study of Pick and Place Operation for Packaging Using Delta Parallel Robot with Two-Fingered Gripper
Mona Mohades Mojtahedi - Arvin Mohammadi - Mehdi Tale Masouleh
A 0.5-V Ultra-Low-Power Low-Pass-filter with Low Noise for ECG detection system
Yasin Heydarzadeh - Mehran Khanehbeygi - Sajad Sohrabian - Ziaddin Daie Koozehkanani
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 40.4.2