A unifying review of deep and shallow anomaly detection
Deep learning approaches to anomaly detection (AD) have recently improved the state of
the art in detection performance on complex data sets, such as large collections of images or …
the art in detection performance on complex data sets, such as large collections of images or …
Deep learning for medical anomaly detection–a survey
Machine learning–based medical anomaly detection is an important problem that has been
extensively studied. Numerous approaches have been proposed across various medical …
extensively studied. Numerous approaches have been proposed across various medical …
Leveraging Deep Learning and IoT big data analytics to support the smart cities development: Review and future directions
The rapid growth of urban populations worldwide imposes new challenges on citizens' daily
lives, including environmental pollution, public security, road congestion, etc. New …
lives, including environmental pollution, public security, road congestion, etc. New …
Deep learning for anomaly detection: A survey
R Chalapathy, S Chawla - arXiv preprint arXiv:1901.03407, 2019 - arxiv.org
Anomaly detection is an important problem that has been well-studied within diverse
research areas and application domains. The aim of this survey is two-fold, firstly we present …
research areas and application domains. The aim of this survey is two-fold, firstly we present …
Heart sound classification based on improved MFCC features and convolutional recurrent neural networks
Heart sound classification plays a vital role in the early detection of cardiovascular disorders,
especially for small primary health care clinics. Despite that much progress has been made …
especially for small primary health care clinics. Despite that much progress has been made …
Deep learning for time series anomaly detection: A survey
Time series anomaly detection has applications in a wide range of research fields and
applications, including manufacturing and healthcare. The presence of anomalies can …
applications, including manufacturing and healthcare. The presence of anomalies can …
Speech technology for healthcare: Opportunities, challenges, and state of the art
Speech technology is not appropriately explored even though modern advances in speech
technology—especially those driven by deep learning (DL) technology—offer …
technology—especially those driven by deep learning (DL) technology—offer …
Deep learning methods for heart sounds classification: a systematic review
The automated classification of heart sounds plays a significant role in the diagnosis of
cardiovascular diseases (CVDs). With the recent introduction of medical big data and …
cardiovascular diseases (CVDs). With the recent introduction of medical big data and …
CardioXNet: A novel lightweight deep learning framework for cardiovascular disease classification using heart sound recordings
The alarmingly high mortality rate and increasing global prevalence of cardiovascular
diseases (CVDs) signify the crucial need for early detection schemes. Phonocardiogram …
diseases (CVDs) signify the crucial need for early detection schemes. Phonocardiogram …
Classification of heart sound signals using a novel deep WaveNet model
Background and objectives The high mortality rate and increasing prevalence of heart valve
diseases globally warrant the need for rapid and accurate diagnosis of such diseases …
diseases globally warrant the need for rapid and accurate diagnosis of such diseases …