6 papers
Forward-Only Convolutional Neural Networks with Learnable Channel-Class Assignment
Mohammadnavid Ghader, Saeed Reza Kheradpisheh, Bahar Farahani +1
The Forward-Forward (FF) algorithm offers a biologically inspired alternative to backpropagation by replacing gradient-based credit assignment with local, forward-only objectives.…
A Multiplication-Free Spike-Time Learning Algorithm and its Efficient FPGA Implementation for On-Chip SNN Training
Maryam Mirsadeghi, Mojtaba Mirbagheri, Saeed Reza Kheradpisheh
Spiking Neural Networks (SNNs) offer a biologically inspired foundation for low-power, event-driven intelligence, yet their direct on-chip supervised training remains a key hardwar…
Persian-Phi: Efficient Cross-Lingual Adaptation of Compact LLMs via Curriculum Learning
Amir Mohammad Akhlaghi, Amirhossein Shabani, Mostafa Abdolmaleki +1
The democratization of AI is currently hindered by the immense computational costs required to train Large Language Models (LLMs) for low-resource languages. This paper presents Pe…
Advanced Physics-Informed Neural Network with Residuals for Solving Complex Integral Equations
Mahdi Movahedian Moghaddam, Kourosh Parand, Saeed Reza Kheradpisheh
In this paper, we present the Residual Integral Solver Network (RISN), a novel neural network architecture designed to solve a wide range of integral and integro-differential equat…
Backpropagation-free Spiking Neural Networks with the Forward-Forward Algorithm
Mohammadnavid Ghader, Saeed Reza Kheradpisheh, Bahar Farahani +1
Spiking Neural Networks (SNNs) offer a biologically inspired computational paradigm that emulates neuronal activity through discrete spike-based processing. Despite their advantage…
Detecting Cadastral Boundary from Satellite Images Using U-Net model
Neda Rahimpour Anaraki, Maryam Tahmasbi, Saeed Reza Kheradpisheh
Finding the cadastral boundaries of farmlands is a crucial concern for land administration. Therefore, using deep learning methods to expedite and simplify the extraction of cadast…