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RL-PDNN: Reinforcement Learning for Privacy-Aware Distributed Neural Networks in IoT Systems
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Due to their high computational and memory demand, deep learning applications are mainly restricted to high-performance units, e.g., cloud and edge servers. Particularly, in Internet of Things (IoT) systems, the data ...
Image Steganography: A Review of the Recent Advances
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Image Steganography is the process of hiding information which can be text, image or video inside a cover image. The secret information is hidden in a way that it not visible to the human eyes. Deep learning technology, ...
Deep Reinforcement Learning for Network Selection over Heterogeneous Health Systems
(
IEEE Computer Society
, 2022 , Article)
Smart health systems improve our quality oflife by integrating diverse information and technologies into health and medical practices. Such technologies can significantly improve the existing health services. However, ...
On Designing Smart Agents for Service Provisioning in Blockchain-powered Systems
(
IEEE Computer Society
, 2021 , Article)
Service provisioning systems assign users to service providers according to allocation criteria that strike an optimal trade-off between users Quality of Experience (QoE) and the operation cost endured by providers. These ...
A review of deep learning-based detection methods for COVID-19
(
Elsevier Ltd
, 2022 , Article)
COVID-19 is a fast-spreading pandemic, and early detection is crucial for stopping the spread of infection. Lung images are used in the detection of coronavirus infection. Chest X-ray (CXR) and computed tomography (CT) ...
Transfer learning with deep Convolutional Neural Network (CNN) for pneumonia detection using chest X-ray
(
MDPI AG
, 2020 , Article)
Pneumonia is a life-threatening disease, which occurs in the lungs caused by either bacterial or viral infection. It can be life-endangering if not acted upon at the right time and thus the early diagnosis of pneumonia is ...
Field data forecasting using lstm and bi-lstm approaches
(
MDPI
, 2021 , Article)
Water, an essential resource for crop production, is becoming increasingly scarce, while cropland continues to expand due to the world's population growth. Proper irrigation scheduling has been shown to help farmers improve ...
DL-CRC: Deep learning-based chest radiograph classification for covid-19 detection: A novel approach
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
With the exponentially growing COVID-19 (coronavirus disease 2019) pandemic, clinicians continue to seek accurate and rapid diagnosis methods in addition to virus and antibody testing modalities. Because radiographs such ...
MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network
(
Springer Science and Business Media Deutschland GmbH
, 2022 , Article)
Electroencephalogram (EEG) signals suffer substantially from motion artifacts when recorded in ambulatory settings utilizing wearable sensors. Because the diagnosis of many neurological diseases is heavily reliant on clean ...
An optimized algorithm for optimal power flow based on deep learning
(
Elsevier
, 2021 , Article)
With the increasing requirements for power system transient stability assessment, the research on power system transient stability assessment theory and methods requires not only qualitative conclusions about system transient ...