A systematic literature review of IoT time series anomaly detection solutions
A Sgueglia, A Di Sorbo, CA Visaggio… - Future Generation …, 2022 - Elsevier
The rapid spread of the Internet of Things (IoT) devices has prompted many people and
companies to adopt the IoT paradigm, as this paradigm allows the automation of several …
companies to adopt the IoT paradigm, as this paradigm allows the automation of several …
Deep learning approaches for video compression: a bibliometric analysis
Every data and kind of data need a physical drive to store it. There has been an explosion in
the volume of images, video, and other similar data types circulated over the internet. Users …
the volume of images, video, and other similar data types circulated over the internet. Users …
MAG-D: A multivariate attention network based approach for cloud workload forecasting
The Coronavirus pandemic and the work-from-home have drastically changed the working
style and forced us to rapidly shift towards cloud-based platforms & services for seamless …
style and forced us to rapidly shift towards cloud-based platforms & services for seamless …
E2LG: a multiscale ensemble of LSTM/GAN deep learning architecture for multistep-ahead cloud workload prediction
P Yazdanian, S Sharifian - The Journal of Supercomputing, 2021 - Springer
Efficient resource demand prediction and management are two main challenges for cloud
service providers in order to control dynamic autoscaling and power consumption in recent …
service providers in order to control dynamic autoscaling and power consumption in recent …
Accurate performance prediction of IoT communication systems for smart cities: An efficient deep learning based solution
Abstract The Internet of Things (IoT), owing to its ability to support sustainability in various
fields, has recently been considered one of the most important components of the …
fields, has recently been considered one of the most important components of the …
The deep learning solutions on lossless compression methods for alleviating data load on IoT nodes in smart cities
Networking is crucial for smart city projects nowadays, as it offers an environment where
people and things are connected. This paper presents a chronology of factors on the …
people and things are connected. This paper presents a chronology of factors on the …
Quantitative analysis of Raman spectra for glucose concentration in human blood using Gramian angular field and convolutional neural network
Q Wang, F Pian, M Wang, S Song, Z Li, P Shan… - Spectrochimica Acta Part …, 2022 - Elsevier
In this study, convolutional neural network based on Gramian angular field (GAF-CNN) was
firstly proposed. The 1-D Raman spectral data was converted into images and used for …
firstly proposed. The 1-D Raman spectral data was converted into images and used for …
Deep recurrent neural network-based autoencoder for photoplethysmogram artifacts filtering
Recently, the need for fast, cost-effective, convenient, and non-invasive cardiovascular
analysis techniques has been the primary and most attractive reason to use …
analysis techniques has been the primary and most attractive reason to use …
Defenses against perception-layer attacks on iot smart furniture for impaired people
Internet of Things (IoT) is becoming highly supportive in innovative technological solutions
for assisting impaired people. Some of these IoT solutions are still in a prototyping phase …
for assisting impaired people. Some of these IoT solutions are still in a prototyping phase …