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The Emergence of Hybrid Edge-Cloud Computing for Energy Efficiency in Buildings
(
Springer Science and Business Media Deutschland GmbH
, 2022 , Conference)
Edge computing is attracting an increasing attention presently even though most of the building energy efficiency solutions are still using cloud computing for gathering, pre-processing and analyzing energy data. However, ...
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 ...
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 ...
Biosignal time-series analysis
(
Elsevier
, 2022 , Book chapter)
In this chapter, recent state-of-the-art techniques in biosignal time-series analysis will be presented. We shall start with the problem of patient-specific ECG beat classification where the objective is to discriminate ...
Uncertainty awareness in transmission line fault analysis: A deep learning based approach
(
Elsevier Ltd
, 2022 , Article)
With the expansion of the modern power system, it is of increasing significance to analyze the faults in the transmission lines. As the transmission line is the most exposed element of a power system, it is prone to different ...
A comparative analysis to forecast carbon dioxide emissions
(
Elsevier Ltd
, 2022 , Article)
Despite the growing knowledge and commitment to climate change, carbon dioxide (CO2) emissions continue to rise dramatically throughout the planet. In recent years, the consequences of climate change have become more ...
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 ...
Deep learning techniques for liver and liver tumor segmentation: A review
(
Elsevier
, 2022 , Article)
Liver and liver tumor segmentation from 3D volumetric images has been an active research area in the medical image processing domain for the last few decades. The existence of other organs such as the heart, spleen, stomach, ...
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 Overview of Deep Learning Methods Used in Vibration-Based Damage Detection in Civil Engineering
(
Springer
, 2022 , Conference)
This paper presents a brief overview of vibration-based damage identification studies based on Deep Learning (DL) in civil engineering structures. The presence, type, size, and propagation of structural damage on civil ...






