794 citations
- Institute for Research in Fundamental SciencesIR192 papers
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35 papers · 1 filter
Fusion techniques of time frequency-based images to predict the outcome of rTMS depression therapy
Wael Korani, Md Fahimul Kabir Chowdhury, Mohammed Aledhari +2
Depression is a mental condition that can lead to suicide and self-harm. Predicting the outcome of depression treatment is one of the most difficult tasks for clinicians. Among var…
Exploiting Expertise of Non-Expert and Diverse Agents in Social Bandit Learning: A Free Energy Approach
Erfan Mirzaei, Seyed Pooya Shariatpanahi, Alireza Tavakoli +2
Personalized AI-based services involve a population of individual reinforcement learning agents. However, most reinforcement learning algorithms focus on harnessing individual lear…
IoMT-based Automated Leukemia Classification using CNN and Higher Order Singular Value
Shabnam Bagheri Marzijarani, Mohammad Zolfaghari, Hedieh Sajedi
The Internet of Things (IoT) is a concept by which objects find identity and can communicate with each other in a network. One of the applications of the IoT is in the field of med…
Multimodal signal fusion for stress detection using deep neural networks: a novel approach for converting 1D signals to unified 2D images
Yasin Hasanpoor, Bahram Tarvirdizadeh, Khalil Alipour +1
This study introduces a novel method that transforms multimodal physiological signalsphotoplethysmography (PPG), galvanic skin response (GSR), and acceleration (ACC) into 2D image…
Argos: A Decentralized Federated System for Detection of Traffic Signs in CAVs
Seyed Mahdi Haji Seyed Hossein, Alireza Hosseini, Soheil Hajian Manesh +1
Connected and automated vehicles generate vast amounts of sensor data daily, raising significant privacy and communication challenges for centralized machine learning approaches in…
OptiGradTrust: Byzantine-Robust Federated Learning with Multi-Feature Gradient Analysis and Reinforcement Learning-Based Trust Weighting
Mohammad Karami, Fatemeh Ghassemi, Hamed Kebriaei +1
Federated Learning (FL) enables collaborative model training across distributed medical institutions while preserving patient privacy, but remains vulnerable to Byzantine attacks a…