Transforming large-size to lightweight deep neural networks for IoT applications
Deep Neural Networks (DNNs) have gained unprecedented popularity due to their high-
order performance and automated feature extraction capability. This has encouraged …
order performance and automated feature extraction capability. This has encouraged …
Intelligent wearable systems: Opportunities and challenges in health and sports
Wearable devices, or wearables, designed to be attached to the human body, can gather
personalized real-time data and continuously monitor an individual's health status and …
personalized real-time data and continuously monitor an individual's health status and …
CovidDeep: SARS-CoV-2/COVID-19 test based on wearable medical sensors and efficient neural networks
S Hassantabar, N Stefano, V Ghanakota… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
The novel coronavirus (SARS-CoV-2) has led to a pandemic. The current testing regime
based on Reverse Transcription-Polymerase Chain Reaction for SARS-CoV-2 has been …
based on Reverse Transcription-Polymerase Chain Reaction for SARS-CoV-2 has been …
Machine learning for multimodal mental health detection: a systematic review of passive sensing approaches
As mental health (MH) disorders become increasingly prevalent, their multifaceted
symptoms and comorbidities with other conditions introduce complexity to diagnosis, posing …
symptoms and comorbidities with other conditions introduce complexity to diagnosis, posing …
SCANN: Synthesis of compact and accurate neural networks
Deep neural networks (DNNs) have become the driving force behind recent artificial
intelligence (AI) research. With the help of a vast amount of training data, neural networks …
intelligence (AI) research. With the help of a vast amount of training data, neural networks …
GPTFX: A Novel GPT-3 based framework for mental health detection and explanations
This paper introduces a novel approach GPTFX, an AI-based mental detection with GPT
frameworks. This approach leverages GPT embeddings and the fine-tuning of GPT-3. This …
frameworks. This approach leverages GPT embeddings and the fine-tuning of GPT-3. This …
DOCTOR: A multi-disease detection continual learning framework based on wearable medical sensors
Modern advances in machine learning (ML) and wearable medical sensors (WMSs) in edge
devices have enabled ML-driven disease detection for smart healthcare. Conventional ML …
devices have enabled ML-driven disease detection for smart healthcare. Conventional ML …
An Improved Global–Local Fusion Network for Depression Detection Telemedicine Framework
In recent years, remote depression detection is becoming a new favorite of the Internet of
Things because of its promise. However, deployable and sensitive information security has …
Things because of its promise. However, deployable and sensitive information security has …
Powerpruning: Selecting weights and activations for power-efficient neural network acceleration
Deep neural networks (DNNs) have been successfully applied in various fields. A major
challenge of deploying DNNs, especially on edge devices, is power consumption, due to the …
challenge of deploying DNNs, especially on edge devices, is power consumption, due to the …
Detecting mental disorders with wearables: A large cohort study
Depression and anxiety are among the most prevalent mental disorders, and they are
usually interconnected. Although these mental disorders have drawn increasing attention …
usually interconnected. Although these mental disorders have drawn increasing attention …