Improving vision anomaly detection with the guidance of language modality
Recent years have seen a surge of interest in anomaly detection for tackling industrial defect
detection, event detection, etc. However, existing unsupervised anomaly detectors …
detection, event detection, etc. However, existing unsupervised anomaly detectors …
A comparison study on training optimization algorithms in the biLSTM neural network for classification of PCG signals
A trained neural network classifier is often used to detect cardiac problems by the
classification of heart sound signals, also known as phonocardiogram (PCG) signals. The …
classification of heart sound signals, also known as phonocardiogram (PCG) signals. The …
Diffusion denoising process for perceptron bias in out-of-distribution detection
Out-of-distribution (OOD) detection is a crucial task for ensuring the reliability and safety of
deep learning. Currently, discriminator models outperform other methods in this regard …
deep learning. Currently, discriminator models outperform other methods in this regard …
Abnormal event detection via feature expectation subgraph calibrating classification in video surveillance scenes
O Ye, J Deng, Z Yu, T Liu, L Dong - IEEE Access, 2020 - ieeexplore.ieee.org
At present, the existing abnormal event detection models based on deep learning mainly
focus on data represented by a vectorial form, which pay little attention to the impact of the …
focus on data represented by a vectorial form, which pay little attention to the impact of the …
Quran reciter identification: A deep learning approach
Speech-based intelligent systems using deep learning are becoming increasingly important
due to their wide range of applications in our routine life. Most of the efforts on voice signal …
due to their wide range of applications in our routine life. Most of the efforts on voice signal …
Classification of phonocardiogram based on multi-view deep network
A phonocardiogram (PCG) is a plot of high-fidelity recording of the sounds of the heart
obtained using an electronic stethoscope that is highly valuable in clinical medicine. It can …
obtained using an electronic stethoscope that is highly valuable in clinical medicine. It can …
LEPCNet: A lightweight end-to-end PCG classification neural network model for wearable devices
Wearable intelligent phonocardiogram (PCG) sensors provide a noninvasive method for
long-term monitoring of cardiac status, which is crucial for the early detection of …
long-term monitoring of cardiac status, which is crucial for the early detection of …
Heart sound signal recovery based on time series signal prediction using a recurrent neural network in the long short-term memory model
In this research, we propose a method for recovering heart sound signals that comprises the
long short-term memory prediction model based on the recurrent neuron network …
long short-term memory prediction model based on the recurrent neuron network …
A primer on artificial intelligence for the paediatric cardiologist
A Gearhart, S Gaffar, AC Chang - Cardiology in the Young, 2020 - cambridge.org
The combination of pediatric cardiology being both a perceptual and a cognitive
subspecialty demands a complex decision-making model which makes artificial intelligence …
subspecialty demands a complex decision-making model which makes artificial intelligence …
Detection of heart sound murmurs and clinical outcome with bidirectional long short-term memory networks
Heart sound recordings are a key non-invasive tool to detect both congenital and acquired
heart conditions. As part of the George B. Moody PhysioNet Challenge 2022, we present an …
heart conditions. As part of the George B. Moody PhysioNet Challenge 2022, we present an …