Publications by Saleh Baghersalimi

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Epilepsy is one of the most prevalent paroxystic neurological disorders. It is characterized by the occurrence of spontaneous seizures. About 1 out of 3 patients have drug-resistant epilepsy, thus their seizures cannot be controlled by medication. Automati ...

Epileptic seizure detection and monitoring is critical in healthcare, particularly for individuals requiring continuous oversight. Current methods, primarily based on electroencephalogram (EEG) technologies, face limitations due to their complexity in term ...

The acquisition of survey responses is a crucial component in conducting research aimed at comprehending public opinion. However, survey data collection can be arduous, time-consuming, and expensive, with no assurance of an adequate response rate. In this ...

The development of low-power wearable systems requires specialized techniques to accommodate their unique requirements and constraints. While significant advancements have been made in the inference phase of artificial intelligence, the training phase rema ...

In healthcare, data privacy of patients regulations prohibits data from being moved outside the hospital, preventing international medical datasets from being centralized for AI training. Federated learning (FL) is a data privacy-focused method that trains ...

Recent state-of-the-art methods for skin lesion segmentation are based on convolutional neural networks (CNNs). Even though these CNN-based segmentation approaches are accurate, they are computationally expensive. In this paper, we address this problem and ...

In federated learning systems, the unexpected quitting of participants is inevitable. Such quittings generally do not incur serious consequences in horizontal federated learning (HFL), but they do damage to vertical federated learning (VFL), which has been ...

This paper addresses the problem of automatic facial expression recognition in videos, where the goal is to predict discrete emotion labels best describing the emotions expressed in short video clips. Building on a pre-trained convolutional neural network ...

Integrating low-power wearable systems into routine health monitoring is an ongoing challenge. Recent advances in the computation capabilities of wearables make it possible to target complex scenarios by exploiting multiple biosignals and using high-perfor ...

Saleh Baghersalimi

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Personalized Real-Time Federated Learning for Epileptic Seizure Detection

Distributed Machine Learning Targeting Embedded Systems for Epilepsy Detection

Predicting Survey Response with Quotation-based Modeling: A Case Study on Favorability towards the United States

Layer-Wise Learning Framework for Efficient DNN Deployment in Biomedical Wearable Systems

Decentralized Federated Learning for Epileptic Seizures Detection in Low-Power Wearable Systems

DermoNet: densely linked convolutional neural network for efficient skin lesion segmentation

PlugVFL: Robust and IP-Protecting Vertical Federated Learning against Unexpected Quitting of Parties

G2-VER: Geometry Guided Model Ensemble for Video-based Facial Expression Recognition

M2SKD: Multi-to-Single Knowledge Distillation of Real-Time Epileptic Seizure Detection for Low-Power Wearable Systems