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AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives
(
Springer Nature
, 2022 , Article)
In theory, building automation and management systems (BAMSs) can provide all the components and functionalities required for analyzing and operating buildings. However, in reality, these systems can only ensure the control ...
Deep and transfer learning for building occupancy detection: A review and comparative analysis
(
Elsevier
, 2022 , Article)
The building internet of things (BIoT) is quite a promising concept for curtailing energy consumption, reducing costs, and promoting building transformation. Besides, integrating artificial intelligence (AI) into the BIoT ...
Machine learning-based management of electric vehicles charging: Towards highly-dispersed fast chargers
(
MDPI AG
, 2020 , Article)
Coordinated charging of electric vehicles (EVs) improves the overall efficiency of the power grid as it avoids distribution system overloads, increases power quality, and decreases voltage fluctuations. Moreover, the ...
Convolutional Sparse Support Estimator-Based COVID-19 Recognition from X-Ray Images
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Coronavirus disease (COVID-19) has been the main agenda of the whole world ever since it came into sight. X-ray imaging is a common and easily accessible tool that has great potential for COVID-19 diagnosis and prognosis. ...
Thermal Change Index-Based Diabetic Foot Thermogram Image Classification Using Machine Learning Techniques
(
MDPI
, 2022 , Article)
Diabetes mellitus (DM) can lead to plantar ulcers, amputation and death. Plantar foot thermogram images acquired using an infrared camera have been shown to detect changes in temperature distribution associated with a ...
COV-ECGNET: COVID-19 detection using ECG trace images with deep convolutional neural network
(
Springer Science and Business Media Deutschland GmbH
, 2022 , Article)
The reliable and rapid identification of the COVID-19 has become crucial to prevent the rapid spread of the disease, ease lockdown restrictions and reduce pressure on public health infrastructures. Recently, several methods ...
MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network
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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 ...
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 ...
COVID-19 infection map generation and detection from chest X-ray images
(
Springer Science and Business Media Deutschland GmbH
, 2021 , Article)
Computer-aided diagnosis has become a necessity for accurate and immediate coronavirus disease 2019 (COVID-19) detection to aid treatment and prevent the spread of the virus. Numerous studies have proposed to use Deep ...
Reliable tuberculosis detection using chest X-ray with deep learning, segmentation and visualization
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Tuberculosis (TB) is a chronic lung disease that occurs due to bacterial infection and is one of the top 10 leading causes of death. Accurate and early detection of TB is very important, otherwise, it could be life-threatening. ...