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A Deep Learning Approach for Vital Signs Compression and Energy Efficient Delivery in mhealth Systems
( Institute of Electrical and Electronics Engineers Inc. , 2018 , Article)© 2013 IEEE. Due to the increasing number of chronic disease patients, continuous health monitoring has become the top priority for health-care providers and has posed a major stimulus for the development of scalable and ... -
Deep Learning Assisted Automated Assessment of Thalassaemia from Haemoglobin Electrophoresis Images
( MDPI , 2022 , Article)Haemoglobin (Hb) electrophoresis is a method of blood testing used to detect thalassaemia. However, the interpretation of the result of the electrophoresis test itself is a complex task. Expert haematologists, specifically ... -
Deep Learning Based Approach For Prediction Of Cloud Resource Needs
(2018 , Professional Masters Project)Cloud computing allows scaling applications to serve dynamic and time-varying workloads and to avoid application performance degradation, while keeping low provisioning costs. But, resource demand of applications need to ... -
A Deep Learning Based Approach To Detect Covert Channels Attacks and Anomaly In New Generation Internet Protocol IPv6
(2020 , Master Thesis)The increased dependence of internet-based technologies in all facets of life challenges the government and policymakers with the need for effective shield mechanism against passive and active violations. Following up ... -
Deep learning based classification of unsegmented phonocardiogram spectrograms leveraging transfer learning
( IOP Publishing Ltd , 2021 , Article)Objective. Cardiovascular diseases (CVDs) are a main cause of deaths all over the world. This research focuses on computer-aided analysis of phonocardiogram (PCG) signals based on deep learning that can enable improved and ... -
Deep learning based identification of DDoS attacks in industrial application
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)Denial of Service (DoS) attacks are very common type of computer attack in the world of internet today. Automatically detecting such type of DDoS attack packets dropping them before passing through is the best prevention ... -
A deep learning based static taint analysis approach for IoT software vulnerability location
( Elsevier B.V. , 2020 , Article)Computer system vulnerabilities, computer viruses, and cyber attacks are rooted in software vulnerabilities. Reducing software defects, improving software reliability and security are urgent problems in the development of ... -
Deep learning for crop yield prediction: a systematic literature review
( Taylor and Francis Ltd. , 2022 , Article Review)Deep Learning has been applied for the crop yield prediction problem, however, there is a lack of systematic analysis of the studies. Therefore, this study aims to provide an overview of the state-of-the-art application ... -
Deep learning for detection of routing attacks in the internet of things
( Atlantis Press , 2018 , Article)Cyber threats are a showstopper for Internet of Things (IoT) has recently been used at an industrial scale. Network layer attacks on IoT can cause significant disruptions and loss of information. Among such attacks, routing ... -
Deep Learning for Reliable Classification of COVID-19, MERS, and SARS from Chest X-ray Images
( Springer , 2022 , Article)Novel coronavirus disease (COVID-19) is an extremely contagious and quickly spreading coronavirus infestation. Severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), which outbreak in 2002 ... -
Deep Learning for RF-Based Drone Detection and Identification: A Multi-Channel 1-D Convolutional Neural Networks Approach
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)Commercial unmanned aerial vehicles, or drones, are getting increasingly popular in the last few years. The fact that these drones are highly accessible to public may bring a range of security and technical issues to ... -
Deep Learning Framework for Liver Segmentation from T1-Weighted MRI Images
( Multidisciplinary Digital Publishing Institute (MDPI) , 2023 , Article)The human liver exhibits variable characteristics and anatomical information, which is often ambiguous in radiological images. Machine learning can be of great assistance in automatically segmenting the liver in radiological ... -
Deep learning in classifying sleep stages
( Institute of Electrical and Electronics Engineers Inc. , 2018 , Conference Paper)This paper presents a deep feed-forward neural network classifier to automatically classify the stages of sleep using raw data taken from a single electropalatogram channel (Fpz-Cz). No features are extracted at all from ... -
Deep Learning IoT Malware Detection Model for IoMT Edge Devices
(2021 , Master Thesis)Internet of Things (IoT) is defined as the massive collection of physical devices being connected to the Internet. IoT has a positive impact in multiple fields, such as health, agriculture, and power management sectors by ... -
Deep learning models for sentiment analysis in arabic
( Association for Computational Linguistics (ACL) , 2015 , Conference Paper)In this paper, deep learning framework is proposed for text sentiment classification in Arabic. Four different architectures are explored. Three are based on Deep Belief Networks and Deep Auto Encoders, where the input ... -
Deep Learning Technique for Congenital Heart Disease Detection Using Stacking-Based CNN-LSTM Models from Fetal Echocardiogram: A Pilot Study
( IEEE , 2023 , Article)Congenital heart defects (CHDs) are a leading cause of death in infants under 1 year of age. Prenatal intervention can reduce the risk of postnatal serious CHD patients, but current diagnosis is based on qualitative criteria, ... -
DEEP LEARNING TECHNIQUES FOR KIDNEY DISEASE DETECTION
(2023 , Master Thesis)Around 10% of the world's population gets affected by Chronic Kidney Diseases or CKDs at some point in their lives and millions die each year due to not having access to affordable treatments and clinical facilities. During ... -
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, ... -
A deep learning-based approach for fault diagnosis of current-carrying ring in catenary system
( Springer Science and Business Media Deutschland GmbH , 2021 , Article)In the Industrial Internet of Things, the deep learning-based methods are used to help solve various problems. The current-carrying ring as one of important components on the catenary system which is always small in the ... -
Deep Learning-Based Conjunctival Melanoma Detection Using Ocular Surface Images
( springer link , 2023 , Article)The human eye could be affected with conjunctival melanoma, which indicates a fatal malignant growth of the eye. Being a very rare disease, there exists a lack of related data in the literature. Also, very few studies ...
